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Graduate Courses

The prefix before the course number—ENGS, ENGG, or ENGM—provides context for the degree requirements that specific courses satisfy and the type of credit granted.

Undergraduate engineering courses are numbered 1 to 99, and may be prerequisites for some graduate courses.

Graduate engineering courses are numbered 100 to 200, and most have prerequisites or other minimum requirements. Courses number 300 and above are considered advanced graduate courses.

Undergraduate engineering science majors may take graduate courses for which they
are qualified. Not all graduate courses, however, can be used to satisfy the AB and/or Engineering Sciences major requirements.

Please be advised that course descriptions, availability, and schedules are subject to change.

  • ENGS 91
    Numerical Methods in Computation

    Description

    A study and analysis of important numerical and computational methods for solving engineering and scientific problems. The course will include methods for solving linear and nonlinear equations, doing polynomial interpolation, evaluating integrals, solving ordinary differential equations, and determining eigenvalues and eigenvectors of matrices. The student will be required to write and run computer programs. ENGS 91 may not be used by mathematics or computer science majors in partial satisfaction of the distributive requirement.

    Prerequisites

    ENGS 20 or COSC 1 and COSC 10; ENGS 22 or MATH 23, or equivalent

    Cross Listed Courses

    COSC 071

    Distribution Code

    QDS

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 12
    Location:

    CUMMINGS 202

    Instructors:

    Thayer Faculty


    Term: Fall 2023
    Time: 12
    Location:

    Cummings 200

    Instructors:

    Simon Shepherd


  • ENGS 92
    Fourier Transforms and Complex Variables

    Description

    Survey of a number of mathematical methods of importance in engineering and physics with particular emphasis on the Fourier transform as a tool for modeling and analysis. Orthogonal function expansions, Fourier series, discrete and continuous Fourier transforms, generalized functions and sampling theory, complex functions and complex integration, Laplace, Z, and Hilbert transforms. Computational Fourier analysis, applications to linear systems, waves, and signal processing.

    Prerequisites

    MATH 46 or ENGS 22 and ENGS 23 or the equivalent

    Cross Listed Courses

    PHYS 070

    Distribution Code

    QDS

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 2
    Location:

    MacLean 132

    Instructors:

    Markus E. Testorf


  • ENGS 93
    Statistical Methods in Engineering

    Description

    The application of statistical techniques and concepts to maximize the amount and quality of information resulting from experiments. After a brief introductory summary of fundamental concepts in probability and statistics, topics considered will include probability distributions, sampling distributions, estimation and confidence intervals for parameters of statistical distributions, hypothesis testing, design and analysis of variance for single and multiple-factor experiments, regression analysis, estimation and confidence intervals for parameters of non-statistical models, and statistical quality control.

    Prerequisites

    MATH 13 or equivalent

    Distribution Code

    QDS

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 11
    Location:

    ECSC 116

    Instructors:

    Wesley Marrero


    Term: Spring 2023
    Time: 10A
    Location:

    CUMMINGS 202

    Instructors:

    Vikrant S. Vaze


    Term: Fall 2023
    Time: 11
    Location:

    Cummings 200

    Instructors:

    Ronald C. Lasky


    Term: Fall 2023
    Time: 3A
    Location:

    Cummings 200

    Instructors:

    Wesley Marrero


    Term: Winter 2024
    Time: 2
    Location:

    ECSC 116

    Instructors:

    Wesley Marrero


  • ENGS 96
    Math for Machine Learning

    Description

    Mathematics for Machine Learning aims to lay the mathematical foundation that are key to understanding the motivations and the implementation ML algorithms. This course will cover the following four broad topics; namely, vector calculus, probability theory, matrix algebra and optimization, in so far as they are used in ML algorithms. The course will conclude with application of these topics to four prototypical ML tasks/algorithms – two in supervised learning (regression using linear models and classification using support vector machine), and two in unsupervised learning (clustering using expectation maximization (EM) and dimensionality reduction using Principal Component Analysis (PCA). Programming at the level of Python and ML software packages (PyTorch, Tensorflow, etc.) will be used to supplement the understanding of the mathematics and algorithms, though the focus of the course will be on developing mathematical foundations and intuitions for the ML algorithms, rather than on developing large-scale applications of ML algorithms.

    Prerequisites

    (MATH 8 or 9) or (MATH 22 or 24); MATH 20 not mandatory; ENGS 20 or COSC 10 preferred

    Distribution Code

    QDS

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: 3A
    Location:

    Cummings 200

    Instructors:

    Peter Chin


  • ENGS 100
    Methods in Applied Mathematics I

    Description

    Concepts and methods used in the treatment of linear equations with emphasis on matrix operations, differential equations, and eigenvalue problems will be developed following a brief review of analytic function theory. Topics include the Fourier integral, finite and infinite dimensional vector spaces, boundary value problems, eigenfunction expansions, Green's functions, transform techniques for partial differential equations, and series solution of ordinary differential equations. Properties and uses of orthogonal polynomials and special functions such as the hypergeometric, Bessel, Legendre, and gamma functions are included. Applications in engineering and physics are emphasized.

    Prerequisites

    ENGS 92 or MATH 33 or MATH 43, with permission of instructor, or the equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 12
    Location:

    CUMMINGS 105

    Instructors:

    Colin R. Meyer


    Term: Winter 2024
    Time: 12
    Location:

    MacLean 201

    Instructors:

    Colin R. Meyer


  • ENGS 102
    Game-theoretic Design, Learning and Engineering

    Description

    Game theory is a field of applied mathematics that describes and analyzes interactive decision-making when two or more parties are involved. Since finding a firm mathematical footing in the 1920’s, it has been applied to a wide variety of fields, including economics, political science, foreign policies, engineering, and machine learning, just to name a few. This course will serve both as an introduction to as well as a survey of applications of game theory, as it has been useful for designing wireless networks, devising market incentives, implementing auction, making resource allocation, designing voting schemes, just to name a few. Therefore, after covering the mathematical foundational work with some measure of mathematical rigor, we will examine many real-world applications, both historical and current. Topics include 2-person/n-person game, cooperative/non-cooperative game, static/dynamic game, strategic/coalitional game, learning in games, price of anarchy, mechanism design and generative adversarial networks and their respective examples and applications. We will also spend some time discussing well known examples such as prisoner’s dilemma, trust game, etc. Further attention will be given to the meaning and the computation complexity of finding of Nash equilibrium as well as Programming at the level of Python and ML software packages (PyTorch, Tensorflow, etc.) will be used to supplement the understanding of the mathematics and algorithms.

    Prerequisites

    MATH 1 or 3, and MATH (8 or 9) or MATH 24, MATH 20 is a plus; and some level of proficiency in a programing language such as C/C++, Julia, Python, R, or MATLAB required

    Notes

    Formerly 199.09

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 3A
    Location:

    ECSC 008

    Instructors:

    Peter Chin


  • ENGS 103
    Operations Research

    Description

    This course provides an overview of a broad range of deterministic and probabilistic operations research models with a focus on engineering applications. Emphasis is on developing strong formulations, understanding key solution concepts, developing efficient algorithms, and grasping the advantages and limitations of each approach. After a brief overview of linear and discrete optimization models, the course covers four main types of techniques: network models, queuing theory, discrete events simulation and game theoretic analysis. Various network models and the corresponding solution algorithms are discussed. Key results and applications of queuing models are presented. Uncertainty associated with real-world modeling is captured through simulation techniques with specific emphasis on discrete events simulation. Equilibrium modeling concepts for strategic form games and extensive form games are introduced as extensions of the core optimization concepts. Application examples are drawn from aerospace, biomedical, civil, computer, electrical, industrial, mechanical, and systems engineering.

    Prerequisites

    ENGS 93 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 2A
    Location:

    CUMMINGS 118

    Instructors:

    Vikrant S. Vaze


    Term: Winter 2024
    Time: 10A
    Location:

    MacLean B01 Zaleski

    Instructors:

    Vikrant S. Vaze


  • ENGS 104
    Optimization Methods for Engineering Applications

    Description

    An introduction to various methods of optimization and their uses in modern engineering. Students will learn to formulate and analyze optimization problems and apply optimization techniques in addition to learning the basic mathematical principles on which these techniques are based. Topic coverage includes linear programming, nonlinear programming, dynamic programming, combinatorial optimization and Monte Carlo methods.

    Prerequisites

    MATH 22 and ENGS 27 or equivalents, or permission of instructor

    Notes

    Not offered 2021-2023
  • ENGS 105
    Computational Methods for Partial Differential Equations I

    Description

    This course concentrates on the numerical solution of partial differential equations commonly encountered in Engineering Sciences. Finite difference and finite element methods are used to solve problems in heat flow, wave propagation, vibrations, fluid mechanics, hydrology, and solid mechanics. The course materials emphasize the systematic generation of numerical methods for elliptic, parabolic, and hyperbolic problems, and the analysis of their stability, accuracy, and convergence properties. Weekly computer exercises will be required to illustrate the concepts discussed in class.

    Prerequisites

    MATH 23 and ENGS 91 (COSC 71), or equivalents

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: 2A
    Location:

    Cummings 105

    Instructors:

    Keith D. Paulsen


  • ENGS 106
    Principles of Machine Learning

    Description

    Machine learning is a set of algorithms in the discipline of AI that enables various systems to learn and improve from data and experience without being explicitly given a set of rules of formulas. It almost seems like magic sometimes, but a distinct goal in this course is to learn that machine learning is not magic but, rather, is based on very rigorous mathematics and engineering principles with a vast number of applications. This course will start with requisite mathematical backgrounds (probability theory, statistics, some basic linear algebra, etc.). Then we will discuss supervised ML models, namely linear regression and classification models, neural network models, and kernel machine models. Finally, we will pivot to unsupervised learning and discuss unsupervised ML learning algorithms, such as probabilistic graphical models, K-clustering algorithm, EM (Expectation Maximization) algorithm, autoencoders, variational inference, PCA/ICA, density estimate, etc. we will also discuss sampling as time permits. Programming at the level of Python and ML software packages (PyTorch, Tensorflow, etc.) will be used to supplement the understanding of the mathematics and algorithms covered in this course . To be sure, the topics covered in this course are relevant for building, understanding, and analyzing wide range of current state-of-the-art machine learning models, but the focus will be on laying a strong theoretical foundation and engineering principles for understanding how the ideas of machine learning are used in fields such as economics, finance, policymaking, and healthcare, just to name a few.

    Prerequisites

    Muti-variable calculus (MATH 8 or MATH 9), linear algebra (MATH 22 or MATH 24), and probability (MATH 20, ENGS 27, or ENGS 93) or equivalent. ENGS 96 encouraged.

    Cross Listed Courses

    COSC 271

    Notes

    Not offered 2021-2023
  • ENGG 107
    Bayesian Statistical Modeling and Computation

    Description

    This course will introduce the Bayesian approach to statistical modeling as well as the computational methods necessary to implement these approaches in research and applications. We will cover methods of statistical learning and inference for a variety of subject area. Students will have the opportunity to apply these concepts and methods in the context of their own research or area of application in the form of a term project.

    Prerequisites

    ENGS 93 or comparable course in probability and statistics; previous programming experience with Matlab, C, S, R or similar language. (MATH/COSC 71, ENGS 91, COSC 70/170 are appropriate ways to fulfill the programming requirement.) We will use R language code.

    Notes

    This course will be offered as ENGS 107 after the 2023-2024 academic year.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 11
    Location:

    ECSC 009

    Instructors:

    Klaus Keller


    Term: Winter 2024
    Time: 11
    Location:

    ECSC 042

    Instructors:

    Klaus Keller


  • ENGS 107
    Bayesian Statistical Modeling and Computation

    Description

    This course will introduce Bayesian approaches to statistical modeling as well as the computational methods necessary to implement these approaches in research and applications. We will cover methods of statistical learning and inference for a variety of subject areas. Students will have the opportunity to apply these concepts and methods in the context of their own research or area of application in the form of a term project.

    Prerequisites

    ENGS 93 or comparable course in probability and statistics; previous programming experience with Matlab, C, S, R, Julia, or similar language. (MATH/COSC 71, ENGS 91, COSC 70/170 are examples for appropriate ways to fulfill the programming requirement.) We will use the R language for code discussions and assignments. R is open source, widely used in statistics, and relatively easy to learn. The prerequisites can be replaced by a permission from the instructor.

    Notes

    This course was previously offered as ENGG 107 and will be offered as ENGS 107 after the 2023-2024 academic year.
  • ENGS 108
    Applied Machine Learning

    Description

    This course will introduce students to modern machine learning techniques as they apply to engineering and applied scientific and technical problems. Techniques such as recurrent neural networks, deep learning, reinforcement learning and online learning will be specifically covered. Theoretical underpinnings such as VC-Dimension, PAC Learning and universal approximation will be covered together with applications to audio classification, image and video analysis, control, signal processing, computer security and complex systems modeling. Students will gain experience with state-of-the-art software systems for machine learning through both assignments and projects. Because of the large overlap in material covered, no student will receive credit for both ENGS 108 and COSC 74/274.

    Prerequisites

    ENGS 20 or equivalent, MATH 22 or equivalent, ENGS 27 or ENGS 93 or equivalent.

    Cross Listed Courses

    QBS 108

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 12
    Location:

    MacLean B01

    Instructors:

    George Cybenko


  • ENGS 109
    High-dimensional Sensing and Learning (HdSL)

    Description

    Sparsity has become a very important concept in recent years in applied mathematics, signal and image processing, and machine learning. The key idea is that many classes of natural signals can be described by only a small number of significant degrees of freedom. This course offers a complete coverage of the recently-emerged field of compressed sensing, which asserts that, if the true signal is sparse to begin with, accurate, robust, and even perfect signal recovery can be achieved from just a few randomized measurements. The course will then proceed to explore how and why this key concept of sparsity may play an important role in sampling theory and learning theory and be applied to a wide variety of real-world applications such as hyper-spectral imaging, cognitive radio, MRI, speech recognition, etc. The focus is on describing the novel ideas that have emerged in sparse recovery with emphasis on theoretical foundations, practical numerical algorithms, and various related signal processing applications. Students from diverse background (engineering, medicine, mathematics, etc.) who are either interested in the subject or want to apply this new theory for their research are encouraged to attend.

    Prerequisites

    (MATH 8 or MATH 9) or (MATH 22 or MATH 24); MATH 20 is a plus; some proficiency of programing language (ENGS 20 or COSC 10)
  • ENGS 110
    Signal Processing

    Description

    Continuous and discrete time signals and systems. The discrete Fourier Transform and the fast Fourier Transform. Linear filtering of signals and noise. Characterization of random signals using correlation functions and power spectral densities. Problems will be assigned which require the use of the computer.

    Prerequisites

    ENGS 32 and ENGS 92 or equivalents

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 3B
    Location:

    CUMMINGS 200

    Instructors:

    Peter Chin


    Term: Spring 2024
    Time: 10
    Location:

    MacLean B01

    Instructors:

    Kelly C Seals


  • ENGS 111
    Digital Image Processing

    Description

    Digital image processing has come into widespread use in many fields, including medicine, industrial process monitoring, military and security applications, as well as satellite observation of the earth. This course will cover many aspects of image processing that students will find valuable in their research or personal interest. Topics will include: image sources, computer representation of images and formats, operations on images, and image analysis. In this course we will stretch the conventional notion of images from 2D pixel arrays to include 3D data sets, and we will explore how one can process such stacks of voxels to produce useful information. This course will also touch on some advanced topics in image processing, which may vary based on students interests. This course will require the completion of a project selected by the student.

    Prerequisites

    ENGS 92 and ENGS 93 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 9L
    Location:

    CUMMINGS 118

    Instructors:

    Xiaoyao Fan


    Term: Spring 2024
    Time: 9L
    Location:

    Cummings 118

    Instructors:

    Xiaoyao Fan


  • ENGS 112
    Modern Information Technologies

    Description

    This course covers current and emerging information technologies, focusing on their engineering design, performance, and application. General topics, such as distributed component and object architectures, wireless networking, web computing, and information security, will be covered. Specific subjects will include Java, CORBA, JINI public key cryptography, web search engine theory and technology, and communications techniques relevant to wireless networking such as Code Division Multiple Access protocols and cellular technology.

    Prerequisites

    ENGS 20, ENGS 93 and ENGS 27 or COSC 60. ENGS 93 can be taken concurrently.
  • ENGG 113
    Image Visualization and Analysis

    Description

    The goal of this course is to introduce graduate level and senior undergraduate students who are working in imaging research to image processing and visualization in 3D using advanced libraries and fully functional software development framework. The most widely used open source software tools for medical image analysis and visualization will be used as the platform: The Insight Registration Segmentation Toolkit (ITK), the Visualization Toolkit (VTK), OpenCV, Qt, and CMake. ITK is an open-source, widely adopted, cross-platform system that provides developers with an extensive suite of software tools for image analysis, including fundamental algorithms for image segmentation and registration. VTK is an open-source, widely adopted, software system for 3D computer graphics, modeling, image processing, volume rendering, scientific visualization, and information visualization. The student will gain understanding of the working of all subroutines and practical application implementing these routines into customized workflow. The course will also introduce the use of OpenCV for applying computer vision and machine learning algorithms to biomedical images and data. Moreover, a full software development environment will be employed to create release-quality applications. This will include the use of source version control to track code changes and bugs, Qt for user interface development, CMake for development environment control, and Visual Studio C++ for the coding environment (Python is also permitted for students with substantial experience working with the language). This state of the art forms the basis for most medical visualization software used today, and students will learn the use of these tools and complete required exercises and projects, with an emphasis on real-world clinical applications.

    Prerequisites

    ENGS 65 or Permission of the Instructor

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: 6B
    Location:

    ECSC 042

    Instructors:

    Michael Jermyn


  • ENGS 114
    Networked Multi-Agent Systems

    Description

    Design and analysis of networked systems comprised of interacting dynamic agents will be considered. Inspired by the cohesive behavior of flocks of birds, we design self-organizing engineering systems that mimic a sense of coordinated motion and the capability of collaborative information processing similar to flocks of birds. Examples include multi-robot networks, social networks, sensor networks, and swarms. The course combines concepts in control theory, graph theory, and complex systems in a unified framework.

    Prerequisites

    ENGS 26, MATH 23, or equivalents plus familiarity with MATLAB

    Notes

    Not offered 2021-2023
  • ENGS 115
    Parallel Computing

    Description

    Parallel computation, especially as applied to large scale problems. The three main topics are: parallel architectures, parallel programming techniques, and case studies from specific scientific fields. A major component of the course is laboratory experience using at least two different types of parallel machines. Case studies will come from applications areas such as seismic processing, fluid mechanics, and molecular dynamics.

    Prerequisites

    ENGS 91 (or COSC 71 or equivalent)

    Notes

    Not offered 2021-2023
  • ENGS 116
    Computer Engineering: Computer Architecture

    Description

    The course provides an introduction to the field of computer architecture. The history of the area will be examined, from the first stored program computer to current research issues. Topics covered will include successful and unsuccessful machine designs, cache memory, virtual memory, pipelining, instruction set design, RISC/CISC issues, and hardware/software tradeoffs. Readings will be from the text and an extensive list of papers. Assignments will include homeworks and a substantial project, intended to acquaint students with open questions in computer architecture.

    Prerequisites

    ENGS 31 and COSC 51; COSC 57, COSC 58, or equivalent recommended

    Cross Listed Courses

    COSC 251

    Notes

    Not offered 2021-2023
  • ENGS 117
    Computational Imaging

    Description

    An examination of computational methods in imaging science. An introduction into imaging theory is presented, including wave propagation, image formation, imaging systems, image quality, and noise sources. Then, advanced topics such as super-resolution imaging, compressed sensing, spectroscopic imaging, wavefront shaping, and holography are studied. Material draws heavily from recent literature. The course incorporates programming projects, critical reviews of journal articles, and construction of original review papers.

    Prerequisites

    ENGS 92 or equivalent

    Notes

    formerly ENGG 117

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 11
    Location:

    Cummings 202

    Instructors:

    Geoffrey P. Luke


  • ENGS 120
    Electromagnetic Waves: Analytical and Modeling Approaches

    Description

    Conceptual development, analysis, and modeling in electromagnetic wave propagation, including boundary conditions, material properties, polarization, radiation, scattering, and phased arrays; emerging research and applications in the areas of electromagnetics and materials.

    Prerequisites

    ENGS 64 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 2
    Location:

    CUMMINGS 105

    Instructors:

    Geoffrey P. Luke


    Term: Winter 2024
    Time: 12
    Location:

    Cummings 105

    Instructors:

    Geoffrey P. Luke


  • ENGG 122
    Advanced Topics in Semiconductor Devices

    Description

    The MOS device structure is the backbone of nearly all modern microelectronics. In this course the gate-insulator-semiconductor structure, commonly referred to as the metal-oxide- semiconductor or MOS structure, will be studied. The historical background of MOS devices and their fabrication will be briefly reviewed, as well as the basic MOS structure for accumulation, depletion and inversion. Advanced issues such as work function, trapped charge, interface traps, non-equilibrium operation and re-equilibration processes will be covered. Analysis of MOS in 1D including capacitance will be performed. The MOSFET will be analyzed with attention on short-channel effects, scaling, drain-induced barrier lowering, etc. The relationship between physics-based MOS device analysis and TCAD modelling will be explored. Other devices utilizing the MOS concept will be discussed, including power devices, CCDs and imaging devices, and FINFETs. The effects of radiation and other reliability issues will also be addressed. There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.

    Prerequisites

    ENGS 60 or equivalents

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: 2A
    Location:

    ECSC 041

    Instructors:

    William J. Scheideler


  • ENGS 123
    Optics

    Description

    The physical principles and engineering applications of optics, with an emphasis on optical systems. Geometric optics: ray tracing, first-order analysis, imaging, radiometry. Wave optics: polarization, interference, diffraction, Fourier optics. Sources and detectors. Fiber optic systems.

    Prerequisites

    ENGS 23 or PHYS 41, and ENGS 92 or equivalent

    Cross Listed Courses

    PHYS 123
  • ENGS 124
    Optical Devices and Systems

    Description

    Light has now taken its place beside electricity as a medium for information technology and for engineering and scientific instrumentation. Applications for light include telecommunications and computers, as well as instrumentation for materials science, and biomedical, mechanical, and chemical engineering. The principles and characteristics of lasers, detectors, lenses, fibers, and modulators will be presented, and their application to specific optical systems introduced. The course will be taught in an interdisciplinary way, with applications chosen from each field of engineering. Students will choose design projects in their field of interest.

    Prerequisites

    ENGS 23

    Cross Listed Courses

    PHYS 124

    Notes

    No notes

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 10A
    Location:

    CUMMINGS 105

    Instructors:

    Jifeng Liu


  • ENGS 125
    Power Electronics and Electromechanical Energy Conversion

    Description

    Controlled use of energy is essential in modern society. As advances in power electronics extend the capability for precise and efficient control of electrical energy to more applications, economic and environmental considerations provide compelling reasons to do so. In this class, the principles of power processing using semiconductor switching are introduced through study of pulse-width-modulated dc-dc converters. High-frequency techniques, such as soft-switching, are analyzed. Magnetic circuit modeling serves as the basis for transformer, inductor, and electric machine design. Electromechanical energy conversion is studied in relation to electrostatic and electromagnetic motor and actuator design. Applications to energy efficiency, renewable energy sources, robotics, and micro-electromechanical systems are discussed. Laboratory exercises lead to a project involving switching converters and/or electric machines.

    Prerequisites

    ENGS 23 and ENGS 32

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 10
    Location:

    Cummings 202

    Instructors:

    Charles R. Sullivan


  • ENGS 126
    Analog Integrated Circuit Design

    Description

    Design methodologies of very large scale integration (VLSI) analog circuits as practiced in industry will be discussed. Topics considered will include practical design considerations such as size and cost; technology processes; modeling of CMOS, bipolar, and diode devices; advanced circuit simulation techniques; basic building blocks; amplifiers; and analog systems. A design project is also required in which the student will design, analyze, and optimize a small analog or mixed analog/digital integrated circuit. This design and some homework assignments will require the student to perform analog and digital circuit simulations to verify circuit operation and performance. Lectures will be supplemented by guest lecturers from industry.

    Prerequisites

    ENGS 32 and ENGS 61, or permission of instructor

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 2A
    Location:

    CUMMINGS 202

    Instructors:

    Kofi M. Odame


    Term: Spring 2024
    Time: 2A
    Location:

    Cummings 202

    Instructors:

    Kofi M. Odame


  • ENGS 127
    Bioelectronics

    Description

    In this course, the fundamentals and applications of micro-and nano-technology-based bioelectronics are introduced. Topics include bioelectricity, biosensor basics, bioelectronic device fabrication, integrated circuit packaging, and in-depth discussions on biopotential electrodes for the recording and stimulation of bioelectricity. Medical device regulations will also be introduced together with safety and ethical issues as critical considerations towards biomedical device translation and commercialization. The course emphasizes the design and analysis methods in developing new bioelectronics. The course project is designed for students to gain experiences and insights in utilizing what’s learned in this course to conduct in-depth critical reviews of recent bioelectronic developments.

    Prerequisites

    ENGS 22 and CHEM 5, or graduate student standing
  • ENGS 128
    Advanced Digital System Design

    Description

    Field-programmable gate arrays (FPGAs) have become a major fabric for implementing digital systems, rivaling application-specific integrated circuits (ASICs) and microprocessors/microcontrollers, particularly in applications requiring special architectures or high data throughput, such as digital signal processing. Hardware description languages (HDLs) have become the dominant method for digital system design. This course will advance the student's understanding of FPGA design flow and ability to perform HDL-based design and implementation on FPGAs. Topics include: FPGA architectures, digital arithmetic, pipelining and parallelism, efficient design using register transfer level coding and IP cores, computer-aided tools for simulation, synthesis, and debugging. The course is graded on a series of laboratory exercises and a final project.

    Prerequisites

    ENGS 31 and ENGS 62 or COSC 51

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: 2
    Location:

    MacLean 132

    Instructors:

    Kendall R Farnham


  • ENGS 129
    Biomedical Circuits and Systems

    Description

    This course covers the fundamental principles of designing electronic instrumentation and measurement systems, including (i) operation and use of a range of transducers (ii) design of sensor interface circuits (iii) operation and use of different analog-to- digital converters (iv) signal processing algorithms and (v) event-driven microcontroller programming. While these engineering principles will be illustrated in the context of biomedical applications, they are equally relevant to other instrumentation and measurement scenarios. In the first half of the course, there are weekly labs during which students build various biomedical devices, such as an ECG-based heart rate monitor, an electronic stethoscope and an automatic blood pressure monitor. Each of these labs underscores a specific principle of instrumentation and measurement system design. The second half of the course is focused on a group project to build a single, moderately-complex piece of instrumentation, such as a blood oxygenation monitor.

    Prerequisites

    ENGS 28 and ENGS 32

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 11
    Location:

    ECSC 042

    Instructors:

    Kofi M. Odame


    Term: Winter 2024
    Time: 11
    Location:

    ECSC 009

    Instructors:

    Kofi M. Odame


  • ENGS 130
    Mechanical Behavior of Materials

    Description

    A study of the mechanical properties of engineering materials and the influence of these properties on the design process. Topics include: tensorial description of stress and strain; elasticity; plastic yielding under multiaxial loading; flow rules for large plastic strains; microscopic basis for plasticity; viscoelastic deformation of polymers; creep; fatigue; and fracture. There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.

    Prerequisites

    ENGS 24 and ENGS 33, or equivalent

    Notes

    Classnotes will be distributed at the start of the class.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 10
    Location:

    Cummings 105

    Instructors:

    Erland M. Schulson


  • ENGS 131
    Science of Solid State Materials

    Description

    This course provides a background in solid state physics and gives students information about modern directions in research and application of solid state science. The course serves as a foundation for more advanced and specialized courses in the engineering of solid state devices and the properties of materials. The main subjects considered are: crystal structure, elastic waves-phonones, Fermi-Dirac and Bose-Einstein statistics, lattice heat capacity and thermal conductivity, electrons in crystals, electron gas heat capacity and thermal conductivity, metals, semiconductors, superconductors, dielectric and magnetic properties, and optical properties. Amorphous solids, recombination, photoconductivity, photoluminescence, injection currents, semiconductor lasers, high temperature superconductors, and elements of semiconductor and superconductor microelectronics are considered as examples. There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.

    Prerequisites

    ENGS 24 or PHYS 24 or CHEM 76 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 2
    Location:

    Cummings 202

    Instructors:

    Jifeng Liu


  • ENGS 132
    Thermodynamics and Kinetics in Condensed Phases

    Description

    This course discusses the thermodynamics and kinetics of phase changes and transport in condensed matter, with the objective of understanding the microstructure of both natural and engineered materials. Topics include phase equilibria, atomic diffusion, interfacial effects, nucleation and growth, solidification of one-component and two-component systems, solubility, precipitation of gases and solids from supersaturated solutions, grain growth, and particle coarsening. Both diffusion-assisted and diffusionless or martensitic transformations are addressed. The emphasis is on fundamentals. Applications span the breadth of engineering, including topics such as polymer transformations, heat treatment of metals, processing of ceramics and semiconductors. Term paper. There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.

    Prerequisites

    ENGS 24 and ENGS 25, or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 10
    Location:

    CUMMINGS 105

    Instructors:

    Erland M. Schulson


    Term: Winter 2024
    Time: 10
    Location:

    Cummings 105

    Instructors:

    Erland M. Schulson


  • ENGS 133
    Methods of Materials Characterization

    Description

    This survey course discusses both the physical principles and practical applications of the more common modern methods of materials characterization. It covers techniques of both microstructural analysis (OM, SEM, TEM, electron diffraction, XRD), and microchemical characterization (EDS, XPS, AES, SIMS, NMR, RBS, and Raman spectroscopy), together with various scanning probe microscopy techniques (AFM, STM, EFM, and MFM). Emphasis is placed on the information that can be obtained together with the limitations of each technique. The course has a substantial laboratory component, including a project involving written and oral reports, and requires a term paper.

    Prerequisites

    ENGS 24 or permission

    Cross Listed Courses

    PHYS 128 and CHEM 137

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 2A
    Location:

    ECSC 005

    Instructors:

    Ian Baker


    Term: Spring 2024
    Time: 2A
    Location:

    ECSC B45

    Instructors:

    Ian Baker


  • ENGS 134
    Nanotechnology

    Description

    Current papers in the field of nanotechnology will be discussed in the context of the course material. In the second half of the term, students will pick a topic of interest and have either individual or small group meetings to discuss literature and research opportunities in this area. The students will prepare a grant proposal in their area of interest. There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.

    Prerequisites

    ENGS 24 or PHYS 19 or CHEM 6, or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 10A
    Location:

    ECSC 041

    Instructors:

    William J. Scheideler


    Term: Winter 2024
    Time: 10A
    Location:

    Cummings 202

    Instructors:

    Jifeng Liu


  • ENGS 135
    Thin Films and Microfabrication Technology

    Description

    This course covers the processing aspects of semiconductor and thin film devices. Growth methods, metallization, doping, insulator deposition, patterning, and analysis are covered. There are two major projects associated with the course — an experimental investigation performed in an area related to the student's research or interests, and a written and oral report on an area of thin film technology.

    Prerequisites

    ENGS 24 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: 12
    Location:

    ECSC 042

    Instructors:

    Hui Fang


  • ENGS 136
    Electrochemical Energy Materials

    Description

    Electrochemical energy materials and devices are playing a vital role in our technology driven society, and are in massive and rapidly growing demand for applications ranging from portable electronics to electric cars, from grid-scale energy storage to defense purposes. This course will give an introduction to the materials developments and characterizations in diverse electrochemical devices, with a focus on various electrode materials and technologies. Topics include, for example, basic principles of electrochemistry; introduction of a series of electrochemical energy storage devices; materials in emerging new battery technologies; photoelectrochemistry and photovoltaic devices. This course focuses on understanding materials science and challenges in modern electrochemical devices. For example, how to engineer the structures and properties of materials to maximize their electrochemical performances? How to characterize structures and compositions of electrochemical materials? The course also includes guest lectures to introduce a variety of energy materials for broad applications, such as solar cells and electrochemical sensing. (It is assumed that students do not have background in electrochemistry) There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.
    Culminating Experience

    Prerequisites

    ENGS 024 or Permission of Instructor

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 3B
    Location:

    ECSC 042

    Instructors:

    Weiyang Li


  • ENGS 137
    Molecular and Materials Design using Density Functional Theory

    Description

    Density Functional Theory (DFT) has become a very powerful tool to compute and predict the properties of molecules and materials. This class will focus on how DFT can be used to compute a large range of materials and molecules properties. The class will expose the fundamentals of DFT but also the practical aspects involved in running computations. A comprehensive number of properties will be studied: structural, mechanical, thermodynamical, optical, electrical and magnetic. The student will learn how to use a DFT code through computational problem sets. The class will as well focus on case studies from the scientific literature presented by students and discussed in class. A strong emphasis will be on the critical assessment of the results obtained by DFT and on the use of the technique to perform prediction and design. There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.
    Includes Lab

    Prerequisites

    ENGS 24 or PHYS 24 or CHEM 76 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 11
    Location:

    ECSC 041

    Instructors:

    Geoffroy T. F. Hautier


  • ENGS 138
    Corrosion and Degradation of Materials

    Description

    This course gives an introduction to the basic principles and applications of corrosion science that underpin extensions to practice. Topics include the thermodynamics and kinetics of electrochemical reactions to the understanding of such corrosion phenomena as passivity, crevice corrosion and pitting, and mechanically assisted corrosion; discussion of methods of corrosion control and prevention; mechanism and application of high-temperature oxidation (dry corrosion); applications to current materials degradation problems in marine environments, petrochemical and metallurgical industries, and energy storage/conversion systems.
    Culminating Experience

    Prerequisites

    ENGS 24

    Notes

    Course was previously ENGG 138

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 3A
    Location:

    ECSC 041

    Instructors:

    Weiyang Li


    Term: Spring 2024
    Time: 3A
    Location:

    ECSC 042

    Instructors:

    Weiyang Li


  • ENGS 139.10
    Polar Science & Engineering: Solidification, Sea Ice, Strength & Fracture of Ice

    Description

    This course focusses on three topics relevant to science and engineering within the polar regions of Earth: solidification of fluids, the nature of sea ice and the strength and fracture of ice .Each topic is treated as a separate module, 8-10 lectures in length.

    Prerequisites

    ENGS 23 or permission of instructor

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: Canceled
    Location:

    ECSC 008

    Instructors:

    Erland M. Schulson


  • ENGS 139.20
    Polar Science & Engineering: Physics & Chemistry of Ice, Polar Glaciology, Remote Sensing

    Description

    This course focusses on three topics relevant to science and engineering within the polar regions of Earth: physics and chemistry of ice, glacial hydrology and remote sensing of polar landscapes., 8-10 lectures in length.

    Prerequisites

    Prerequisites: ENGS 24, general chemistry (full year), or permission of instructor.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 10A
    Location:

    ECSC 005

    Instructors:

    Erland M. Schulson


  • ENGS 142
    Intermediate Solid Mechanics

    Description

    Exact and approximate solutions of the equations of elasticity are developed and applied to the study of stress and deformation in structural and mechanical elements. The topics will include energy methods, advanced problems in torsion and bending, stress concentrations, elastic waves and vibrations, and rotating bodies. Although most applications will involve elastic deformation, post-yield behavior of elastic-perfectly plastic bodies will also be studied. The course will also include numerous applications of finite element methods in solid mechanics.

    Prerequisites

    ENGS 71 or ENGS 76 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 3A
    Location:

    ECSC 041

    Instructors:

    Yan Li


  • ENGS 144
    Engineering Simulation for Mechanical Design and Analysis

    Description

    This course emphasizes the practical application of state-of-the-art engineering simulation tools and techniques for mechanical design and analysis. Students will create virtual prototypes and conduct fluid flow, heat transfer, and structural analyses using sophisticated computational models to predict mechanical performance under real life conditions. The course includes a survey of techniques for coupled multiphysics simulations such as thermo-fluid and fluid-structure interactions. Performance-based, simulation-driven design and design optimization concepts will be introduced. Topics presented in the classroom will be reinforced through hands-on tutorial exercises and the completion of a simulation project.

    Prerequisites

    ENGS 76 plus at least one of ENGS 23, 25, or 34 (or permission of the instructor)

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: 10A
    Location:

    Cummings 118

    Instructors:

    Eric S. Bish


  • ENGS 145
    Modern Control Theory

    Description

    A continuation of ENGS 26, with emphasis on digital control, state-space analysis and design, and optimal control of dynamic systems. Topics include review of classical control theory, discrete-time system theory, discrete modeling of continuous-time systems, transform methods for digital control design, the state-space approach to control system design, optimal control, and effects of quantization and sampling rate on performance of digital control systems. Laboratory exercises reinforce the major concepts; the ability to program a computer in a high-level language is assumed.

    Prerequisites

    ENGS 26

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 10A
    Location:

    ECSC 041

    Instructors:

    Minh Q. Phan


    Term: Fall 2023
    Time: 10A
    Location:

    ECSC 041

    Instructors:

    Minh Q. Phan


    Term: Fall 2024
    Time: 10A
    Location: –
    Instructors:

    Minh Q. Phan


  • ENGS 146
    Computer-Aided Mechanical Engineering Design

    Description

    An investigation of techniques useful in the mechanical design process. Topics include computer graphics, computer-aided design, computer-aided manufacturing, computer-aided (finite element) analysis, and the influence of manufacturing methods on the design process. Project work will be emphasized. Enrollment is limited to 24 students.

    Prerequisites

    ENGS 76

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 3B
    Location:

    MACLEAN 210

    Instructors:

    Eric S. Bish


  • ENGS 147
    Mechatronics

    Description

    Mechatronics is the systems engineering approach to computer-controlled products. This course will integrate digital control theory, real-time computing, software design, sensing, estimation, and actuation through a series of laboratory assignments, complementary lectures, problem sets, and a final project. Topics covered will include microprocessor based real-time computing, digital control, state estimation, signal conditioning, sensors, autonomous navigation, and control architectures for autonomous systems.

    Prerequisites

    ENGS 26 or ENGS 145; two of ENGS 31, ENGS 32, ENGS 33, ENGS 76, or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 3A
    Location:

    MACLEAN 132

    Instructors:

    Laura E. Ray

    Michael A. Kokko


    Term: Spring 2024
    Time: 3A
    Location:

    MacLean 132

    Instructors:

    Michael A. Kokko


  • ENGG 148
    Structural Mechanics

    Description

    Development and application of approximate and "exact" analytical and computational methods of analysis to a variety of structural systems, including trusses, two- and three-dimensional frames, plates and/or shells. Modeling of structural systems as one and multi degree of freedom lumped systems permits analysis under a variety of dynamic loads as well as providing an introduction to vibration analysis.

    Prerequisites

    ENGS 33

    Notes

    Can be used by undergraduates for A.B. course count only

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 10A
    Location:

    ECSC 127

    Instructors:

    Minh Q. Phan


  • ENGG 149
    Introduction to Systems Identification

    Description

    This course provides the fundamentals of system identification theory and its applications to mechanical, electrical, civil, and aerospace systems. Several state-of-the-art identification algorithms in current engineering practice will be studied. The following topics are covered: discrete-time and continuous-time models, state-space and input-output models, Markov parameters, observer Markov parameters, discrete Fourier transform, frequency response functions, singular value decomposition, least-squares parameter estimation, minimal realization theory, observer/Kalman filter identification, closed-loop system identification, nonlinear system identification, recursive system identification, and introduction to adaptive control.

    Prerequisites

    ENGS 22 and ENGS 26, or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: 10A
    Location:

    MacLean 132

    Instructors:

    Minh Q. Phan


  • ENGS 150
    Intermediate Fluid Mechanics

    Description

    Following a review of the basic equations of fluid mechanics, the subjects of potential flow, viscous flows, boundary layer theory, turbulence, compressible flow, and wave propagation are considered at the intermediate level. The course provides a basis for subsequent more specialized studies at an advanced level.

    Prerequisites

    ENGS 25, ENGS 34, or permission of the instructor

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 11
    Location:

    MACLEAN 201 RETTS

    Instructors:

    Colin R. Meyer


    Term: Winter 2024
    Time: 11
    Location:

    MacLean 201

    Instructors:

    Kasia Warburton

    Colin R. Meyer


  • ENGS 151
    Environmental Fluid Mechanics

    Description

    Applications of fluid mechanics to natural flows of water and air in environmentally relevant systems. The course begins with a review of fundamental fluid physics with emphasis on mass, momentum, and energy conservation. These concepts are then utilized to study processes that naturally occur in air and water, such as boundary layers, waves, instabilities, turbulence, mixing, convection, plumes, and stratification. The knowledge of these processes is then sequentially applied to the following environmental fluid systems: rivers and streams, wetlands, lakes and reservoirs, estuaries, the coastal ocean, smokestack plumes, urban airsheds, the lower atmospheric boundary layer, and the troposphere. Interactions between air and water systems are also studied in context, e.g., sea breeze in the context of the lower atmospheric boundary layer.

    Prerequisites

    ENGS 25, ENGS 34, and ENGS 37, or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: CANCELED
    Location: –
    Instructors:

    Benoit Cushman-Roisin


    Term: Spring 2024
    Time: 2A
    Location:

    Cummings 105

    Instructors:

    Benoit Cushman-Roisin


  • ENGS 152
    Magnetohydrodynamics

    Description

    The fluid description of plasmas and electrically conducting fluids including magnetohydrodynamics and two-fluid fluid theory, with applications to laboratory and space plasmas, including magnetostatics, stationary flows, waves, instabilities, and shocks.

    Prerequisites

    PHYS 68 or equivalent, or permission of the instructor

    Cross Listed Courses

    PHYS 115
  • ENGS 153
    Computational Plasma Dynamics

    Description

    Theory and computational techniques used in contemporary plasma physics, especially nonlinear plasma dynamics, including fluid, particle and hybrid simulation approaches as well as linear dispersion codes and data analysis. This is a "hands-on" numerical course; students run plasma simulation codes and do a significant amount of new programming (using MATLAB).

    Prerequisites

    PHYS 68 or equivalent with ENGS 91 or equivalent recommended, or permission of the instructor

    Cross Listed Courses

    PHYS 118

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: Arrange
    Location: –
    Instructors:

    A&S Staff


  • ENGS 155
    Intermediate Thermodynamics

    Description

    The concepts of work, heat and thermodynamic properties are reviewed. Special consideration is given to derivation of entropy through information theory and statistical mechanics. Chemical and phase equilibria are studied and applied to industrial processes. Many thermodynamic processes are analyzed; the concept of exergy is used to evaluate their performance and identify ways to improve their efficiency.

    Prerequisites

    ENGS 25

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: Arrange
    Location: –
    Instructors:

    Ronald C. Lasky


  • ENGS 156
    Heat, Mass, and Momentum Transfer

    Description

    Fundamentals of convection, conduction, radiation, mass, and momentum transport. Basic conservation laws and rate equations in laminar and turbulent flows. Exact solutions. Approximate solutions using boundary layer or integral techniques. Empirical methods. Analysis of engineering systems. There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.

    Prerequisites

    ENGS 25, ENGS 34

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 10A
    Location:

    CUMMINGS 102

    Instructors:

    Ronald C. Lasky


    Term: Winter 2024
    Time: 3B
    Location:

    ECSC 042

    Instructors:

    Alexis R. Abramson


  • ENGS 157
    Chemical Process Design

    Description

    An in-depth exposure to the design of processes featuring chemical and/or biochemical transformations. Topics will feature integration of unit operations, simulation of system performance, sensitivity analysis, and system-level optimization. Process economics and investment return will be emphasized, with extensive use of the computer for simulation and analysis.

    Prerequisites

    ENGS 36

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 10
    Location:

    CUMMINGS 118

    Instructors:

    Mark S. Laser


    Term: Winter 2024
    Time: 10
    Location:

    Cummings 118

    Instructors:

    Mark S. Laser


  • ENGS 158
    Chemical Kinetics and Reactors

    Description

    The use of reaction kinetics, catalyst formulation, and reactor configuration and control to achieve desired chemical transformations. The concepts and methods of analysis are of general applicability. Applications include combustion, fermentations, electrochemistry, and petrochemical reactions.

    Prerequisites

    ENGS 36

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 12
    Location:

    CUMMINGS 118

    Instructors:

    Mark S. Laser


    Term: Spring 2024
    Time: 2
    Location:

    Cummings 202

    Instructors:

    Xin Qi


  • ENGS 159
    Molecular Sensors & Nanodevices in Biomedical Engineering

    Description

    Introduction to fundamentals and major types of molecular sensor systems, scaling laws of device miniaturization, and detection mechanisms, including molecular capture mechanisms; electrical, optical, and mechanical transducers; micro-array analysis of biomolecules; semiconductor and metal nanosensors; microfluidic systems; and microelectromechanical systems (MEMS, BioMEMS) design, fabrication and applications for bioengineering. Three lab sessions are designed to gain hands-on experience on microfluidic chip and soft lithography, gold nanorods-based biomolecular sensors, micro-reactors using colloidal chemistry in engineering of nanoparticles for biomedical applications in sensing and imaging.

    Prerequisites

    ENGS 22, CHEM 6, or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 11
    Location:

    MACLEAN 201 RETTS

    Instructors:

    John Zhang


    Term: Spring 2024
    Time: 11
    Location:

    MacLean 201

    Instructors:

    John Zhang


  • ENGS 160
    Biotechnology and Biochemical Engineering

    Description

    A graduate section of ENGS 35 involving a project and extra class meetings. Not open to students who have taken ENGS 35. Enrollment is limited to 6.

    Prerequisites

    MATH 3, CHEM 5, BIOL 12 or BIOL 13 and permission of the instructor
  • ENGS 161
    Metabolic Engineering

    Description

    Metabolic engineering combines aspects of chemical engineering, systems biology and synthetic biology. This course focuses on developing a quantitative understanding of metabolic processes within the cell. Although metabolism is a complex process, it is determined by a small number of physical constraints, including enzyme activity, mass balance and thermodynamics. In this course you will learn to perform a mass balance, construct and analyze a stoichiometric network, simulate a series of kinetic reactions, and analyze isotope tracer experiments. Key genetic techniques, including CRISPR, will be presented. Computational analysis will be performed using COBRA and Equilibrator via Python and associated tools in the Python Data Science stack. These tools will be applied first to several canonical examples from the metabolic engineering literature and then to a project of your choosing.
    Culminating Experience

    Prerequisites

    Engineering Sciences 35/160 and a non-introductory course in biochemistry or molecular biology, or permission.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 10
    Location:

    ECSC 041

    Instructors:

    Daniel G. Olson


  • ENGS 162
    Basic Biological Circuit Engineering

    Description

    This course will provide a comprehensive introduction to the design, modeling, and experimental implementation of synthetic bio-molecular circuits in living cells, which have wide applications in biotechnology and medicine. Simple but sophisticated synthetic biological circuits will be implemented and tested in microbial cells in the laboratory. Computer aided design, modeling, and simulation will use an industry standard electronic circuit design tool showing how to design, model, and fit actual experimental biological data such that engineering circuit theory and biological experiment agree.
    Design Credit

    Prerequisites

    MATH 3 or MATH 8 or equivalent experience in Basic Calculus, CHEM 5, BIOL 13. Experience in Molecular Biology is useful (e.g. ENGS 35, BIOL 45, & BIOL 46 or equivalent) but not necessary. Experience in Signals and System Modeling is also useful (e.g. ENGS 22) but not necessary.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 11
    Location:

    ECSC 041

    Instructors:

    Rahul Sarpeshkar


    Term: Winter 2024
    Time: 11
    Location:

    ECSC 041

    Instructors:

    Rahul Sarpeshkar


  • ENGS 163
    Advanced Protein Engineering

    Description

    This course will build on molecular engineering fundaments introduced in ENGS 58 and equip students to formulate novel engineered molecules by translating methods into practical design proposals. The three components of any protein engineering effort will be surveyed: host strain, library design, and selective pressure. Both gold standard and novel engineering methodologies will be studied, and tradeoffs among different techniques will be examined through detailed case studies. Data presentation and interpretation skills will be developed by examining current literature focused on proteins with practical utility.

    Prerequisites

    ENGS 58, OR ENGS 160, OR BIOCHEM 101. Equivalent courses accepted with instructor’s permission.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 2
    Location:

    ECSC 041

    Instructors:

    Jiwon Lee


    Term: Winter 2024
    Time: 2
    Location:

    ECSC 041

    Instructors:

    Jiwon Lee


  • ENGS 164
    Tissue Engineering

    Description

    This course will provide an overview of the field of Tissue Engineering, focusing on the development of biological constructs to replace, restore, and regenerate tissue. Content will include key concepts related to tissue structure, cellular fate processes, biomaterials, and the large-scale production of tissue engineered scaffolds. This course will incorporate lectures, quizzes, journal articles, and group projects for students to build a strong background in tissue engineering and experience the steps of designing a tissue engineered construct to be moved to market.
    Culminating Experience

    Prerequisites

    ENGS 56, or ENGS 165, or both ENGS 24 and BIOL 12, or equivalent

    Notes

    This course title and description updated fall 2022

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: 12
    Location:

    ECSC 009

    Instructors:

    Katherine R. Hixon


  • ENGS 165
    Biomaterials

    Description

    Consideration of material problems is perhaps one of the most important aspects of prosthetic implant design. The effects of the implant material on the biological system as well as the effect of the biological environment on the implant must be considered. In this regard, biomaterial problems and the bioelectrical control systems regulating tissue responses to cardiovascular and orthopedic implants will be discussed. Examples of prosthetic devices currently being used and new developments of materials appropriate for future use in implantation will be taken from the literature. There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.

    Prerequisites

    ENGS 24, or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: Tu/Th 8:30AM-10:00AM
    Location:

    MACLEAN 201 RETTS

    Instructors:

    Douglas W. Van Citters


    Term: Spring 2024
    Time: 9L
    Location:

    MacLean 201

    Instructors:

    Alex Boys


  • ENGS 166
    Quantitative Human Physiology

    Description

    This is a comprehensive review of the integrated functions of cells, organs, and systems of the human body, focusing both on physiology and quantitation. The hierarchy of systems is reviewed with basic explanation as well as function-based analysis. The educational goal is to acquire a working knowledge of most major body systems, and an expert level ability for quantitative modeling and measurement of their function.

    Prerequisites

    ENGS 22 or equivalent; BIOL 12 or BIOL 14 or ENGS 30; ENGS 23 or MATH 23 or PEMM 101

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 2A
    Location:

    ECSC 035

    Instructors:

    Kimberley Samkoe


  • ENGS 167
    Medical Imaging

    Description

    A comprehensive introduction to all major aspects of standard medical imaging systems used today. Topics include radiation, dosimetry, x-ray imaging, computed tomography, nuclear medicine, MRI, ultrasound, and imaging applications in therapy. The fundamental mathematics underlying each imaging modality is reviewed and an engineering picture of the hardware needed to implement each system is examined. The course will incorporate a journal club review of research papers, term tests, and a term project to be completed on an imaging system.

    Prerequisites

    ENGS 92 (may be taken conconcurrently)

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 9L
    Location:

    ECSC 009

    Instructors:

    David Gladstone


    Term: Winter 2024
    Time: 9L
    Location:

    Cummings 202

    Instructors:

    David Gladstone


  • ENGG 168
    Biomedical Radiation Transport

    Description

    This course will provide a general overview of radiation transport mechanisms in matter, beginning with a derivation of the Boltzmann radiation transport equation, and examining the various approximations possible. Focus on the single-energy Diffusion approximation will be examined in detail, as it relates to neutron diffusion nuclear reactors and optical photon diffusion. Review of photon diffusion in tissue will be discussed as it relates to tissue spectroscopy and imaging. Fundamental research papers in this field will be presented and reviewed, covering aspects of multiple scattering, Mie scattering, and scattering phase functions. Stochastic model-based approaches will be covered as well, such as the Monte Carlo model. Numerical approaches to solving these models will be introduced.

    Prerequisites

    ENGS 23 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 9L
    Location:

    Cummings 118

    Instructors:

    Petr Bruza


  • ENGS 169
    Intermediate Biomedical Engineering

    Description

    A graduate section of ENGS 57. Students taking the course for graduate credit will be expected to write a research proposal aimed at developing a specific surgical technology. Groups of 2-3 students will work together. The proposal will require an extensive literature review, a detailed proposal of research activities, alternative methods, and timeline, and a detailed budget and budget justification for meeting the research objectives. Weekly meetings will take place between the groups and Professor Halter to discuss progress. By the end of the term the groups are expected to have a complete proposal drafted. Enrollment is limited to 18 students. Not open to students who have taken ENGS 57.

    Prerequisites

    ENGS 23 and ENGS 56 or equivalent

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 10
    Location:

    CUMMINGS 202

    Instructors:

    Ryan J. Halter


    Term: Spring 2024
    Time: 10
    Location:

    ECSC B01

    Instructors:

    Ryan J. Halter


  • ENGS 170
    Neuroengineering

    Description

    This course will introduce students to currently available and emerging technologies for interfacing with the human brain. Students will study the fundamental principles, capabilities and limitations of a range of relevant technologies within the scope of noninvasive brain-computer interfaces, neural implants, neurostimulation, sensory substitution and neuroinformatics. The ethical and societal ramifications of these technologies will also be considered. Applications of neuroengineering technology in medicine will be emphasized such as the diagnosis and treatment of neurological diseases and neural rehabilitation.

    Prerequisites

    ENGS 22 and ENGS 56

    Notes

    Not offered 2021-2023
  • ENGS 171
    Industrial Ecology

    Description

    A product’s environmental impacts result from design, production, and operational choices. Industrial ecology identifies economic ways to improve these environmental impacts, chiefly by designing for circular material flows, improving energy effectiveness and material choice, changing user behavior, systems thinking, and otherwise promoting sustainability. The objective of this course is to do all of the above for a product to conceptually invent or innovate a market- viable alternative. To do this, a broad spectrum of industrial activities is reviewed, including products and services. This course examines to what extent environmental and social concerns have already affected specific industries, and where additional progress can be made. Student activities include a critical review of current literature, participation in class discussion, and a term project in design for the environment.

    Prerequisites

    ENGS 21 and ENGS 37 or instructor permission for MBA students. Students should have a basic understanding of how to progress from initial concept to prototype, and should have a basic understanding of environmental impacts such as pollution and climate change.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 2A
    Location:

    MACLEAN 201 RETTS

    Instructors:

    Benoit Cushman-Roisin


    Term: Winter 2024
    Time: 2A
    Location:

    Cummings 200

    Instructors:

    Benoit Cushman-Roisin


  • ENGS 172
    Climate Change and Engineering

    Description

    Earth’s climate is result of interplay between continental and moving atmospheric and oceanic systems with multiple forcing mechanisms and internal feedbacks. Fundamental heat, mass, and radiative transfer processes impacting the climate system will be examined to understand the drivers of current and past climate. Published regional and global impact projections and adaptation strategies for the future will be examined. Mitigation and sustainable energy will be investigated, and choices on the international, national and local scales will be discussed. Students will be required to actively participate in class by leading class discussions and actively engaging in small group activities. In addition, students will conduct a research project to design an adaptation and mitigation strategy for a community or business in a region of their choice, and will write a term paper and make an oral presentation of their findings.

    Prerequisites

    ENGS 151 or ENGS 156 or EARS 178, or equivalent.

    Notes

    .

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 2
    Location:

    ECSC 041

    Instructors:

    Klaus Keller


    Term: Spring 2024
    Time: 11
    Location:

    ECSC 042

    Instructors:

    Klaus Keller


  • ENGS 172.20
    Techno-economic Analysis in a Developing Country Context

    Description

    This course will address the application of techno-economic analysis (TEA) to evaluate the profitability and broader social and environmental impact of potential business ventures involving technologies located in developing countries. Elements of techno-economic analysis will be discussed, including process design and simulation; profitability analysis; and life-cycle assessment. Aspects unique to developing countries – such as poor infrastructure, financing limitations, and unfavorable government policies – will also be considered. Ongoing review and discussion of illustrative TEA examples, including case studies of actual ventures, will reinforce key concepts. The course will also feature a series of expert guest speakers from industry, academia, and non-profit organizations.

    Notes

    Was ENGG 19904

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 9S
    Location:

    MACLEAN 132

    Instructors:

    Mark S. Laser


    Term: Spring 2024
    Time: 9S
    Location:

    MacLean 132

    Instructors:

    Mark S. Laser


  • ENGS 173
    Energy Utilization

    Description

    Industrial societies are presently powered primarily by fossil fuels. Continuing to supply energy at the rate it is now used will be problematic, regardless of the mix of fossil fuels and alternatives that is used; yet western consumption patterns spreading through the rest of the world and other trends portend large increases in demand for energy services. Increased energy efficiency will be essential for meeting these challenges, both to reduce fossil-fuel consumption and to make significant reliance on alternatives feasible. Technical issues in efficient systems for energy utilization will be surveyed across major uses, with in-depth technical analysis of critical factors determining possible, practical, and economical efficiency improvements in both present technology and potential future developments. Areas addressed include lighting, motors and drive systems, heating, ventilation and air conditioning, transportation, appliances and electronics.
    Culminating Experience

    Prerequisites

    ENGS 22 and at least two of the following: ENGS 25, ENGS 32, ENGS 34, ENGS 44, ENGS 52, ENGS 76, ENGS 104, ENGS 125, ENGS 150, ENGS 155, ENGS 156, and ENGM 184, or permission. ENGS 25 is strongly recommended

    Notes

    Previously ENGG 173

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 10A
    Location:

    CUMMINGS 118

    Instructors:

    Charles R. Sullivan


    Term: Winter 2024
    Time: 10A
    Location:

    Cummings 118

    Instructors:

    Charles R. Sullivan


  • ENGS 174
    Energy Conversion

    Description

    This course will address the science and technology of converting key primary energy sources — fossil fuels, biomass, solar radiation, wind, and nuclear fission and fusion — into fuels, electricity, and usable heat. Each of these topics will be analyzed in a common framework including underlying fundamentals, constraints on cost and performance, opportunities and obstacles for improvement, and potential scale.

    Prerequisites

    ENGS 22 and at least two of the following: ENGS 25, ENGS 32, ENGS 34, ENGS 36, ENGS 44, ENGS 52, ENGS 76, ENGS 104, ENGS 125, ENGS 150, ENGS 155, ENGS 156, and ENGM 184, or permission. ENGS 25 is strongly recommended.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 11
    Location:

    MacLean 132

    Instructors:

    Mark S. Laser


  • ENGS 175
    Energy Systems

    Description

    A consideration of energy futures and energy service supply chains at a systemic level. Dynamic development of demand and supply of primary energy sources and key energy carriers will be considered first assuming continuation of current trends, and then with changes to current trends in order to satisfy constraints such as limiting carbon emissions and changing resource availability. Integrated analysis of spatially-distributed time-variable energy systems will also be addressed, with examples including generation, storage, and distribution of electricity and production of energy from biomass.

    Prerequisites

    ENGS 25, ENGS 51, either ENGG 173 or ENGG 174 or permission of the instructor

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 11
    Location:

    ECSC 042

    Instructors:

    Erin N. Mayfield


    Term: Spring 2024
    Time: 10A
    Location:

    ECSC 042

    Instructors:

    Steven O. Peterson


  • ENGS 177
    Decision-Making under Uncertainty

    Description

    Decision Making under Uncertainty introduces the foundational ideas of making good decisions despite an unknown environment. This course will start with a review of probability and will mainly focus on solution techniques for single-stage and sequential decision problems. Specifically, the course will be divided into four main parts: (1) overview and probabilistic models; (2) solution techniques for single-stage decision problems; (3) model-based solution techniques for sequential decision problems; and (4) model-free solution techniques for sequential decision problems. The approaches for solving decision-making problems covered in this course are relevant for a wide range of fields including engineering, computer science, finance, supply chain management, transportation, and healthcare. The goal of this course is to provide students with the required knowledge to apply solution techniques in real-world situations.

    Prerequisites

    ENGS 103 or permission of the instructor. Additionally, students should be proficient in a programming language such as Julia, Python, R, or MATLAB.

    Notes

    This course was previously offered as ENGG 177.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: 3A
    Location:

    Cummings 202

    Instructors:

    Wesley Marrero


  • ENGM 178
    Technology Assessment

    Description

    This project course is grounded in technology-focused areas and provides an opportunity for teams of students to conduct a thorough analysis of prevalent and emerging technologies in fields of critical interest such as health, energy, the environment, and other complex systems and then to recommend and justify actions for its further development. Technology in an assigned application field will be analyzed by each student team, along with emerging, complementary and competing technologies, leading to 1) findings of those impediments and incentives for its further development, 2) identification and quantification of the societal and/or commercial benefits achievable from further development, and 3) recommendations for action in research funding, product and market development, public policy, and the like, that would most rapidly achieve the identified societal and/or commercial benefits.

    Prerequisites

    No prerequisite

    Notes

    Cannot be used to satisfy any A.B. degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 10A
    Location:

    Cummings 200

    Instructors:

    Eric S. Bish


  • ENGM 179.10
    Strategy

    Description

    Strategy entails shaping and managing factors that are critical to the long-term success of an organization. Decision makers must formulate and implement strategy for the organization as a whole, and guide the organization in navigating strategic challenges as markets and technologies change. This course covers key frameworks and principles for formulating and implementing strategy in single-business and multi-business firms, with respect to the external context in which a firm competes and its internal operations. Applying this material to case studies and other company examples will help you to develop your skills in strategic analysis.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Wed/Thur 3:30-5:00 PM
    Location:

    Stoneman (Tuck)

    Instructors:

    Tuck Faculty


  • ENGM 179.20
    Organizational Behavior

    Description

    Organizations are complex social systems that bring together tasks, structures, people and culture. Their success depends on people interacting within this system to achieve common goals. This course will provide you with conceptual frameworks for increasing individual, team, and organizational performance. More specific learning goals include: a) to increase your knowledge about individual, interpersonal and group behavior in complex organizations; b) to increase your awareness of your own and others’ assumptions, motivations, attitudes, values, emotions and behavior in human interaction; c) to increase your skill in diagnosing the structural and behavioral antecedents of destructive behavior in organizations, and prescribing effective action to remedy those problems; and d) to manage this complex system in service of achieving strategic goals. We will address these goals by learning about the underlying psychological and sociological foundations of human behavior and will engage in case study discussions and interactive exercises to help you build effective leadership skills.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Wed/Thur 3:30-5:00 PM
    Location:

    Stoneman (Tuck)

    Instructors:

    Tuck Faculty


  • ENGM 180
    Accounting and Finance

    Description

    This course provides an integrated exploration of financial accounting and finance. Financial accounting refers to the system a firm uses to both record its transactions and report its results to investors and other users of financial statements. Finance refers to the financial aspects of managerial decisions and the capital markets in which firms raise funds for investment to provide practical tools for financial decision making and valuation.  

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: M/T 8:30 - 10
    Location:

    MURDGH STONEMAN

    Instructors:

    Tuck Faculty


    Term: Spring 2024
    Time: M/T 8:30 - 10:00am
    Location:

    MURDGH STONEMAN

    Instructors:

    Felipe Severino

    Joseph Gerakos


  • ENGM 181
    Marketing

    Description

    This course introduces the role of marketing within business firms. Case studies drawn from a wide variety of consumer and industrial products and services provide an opportunity for students to apply concepts and techniques developed in assigned readings. Specific topics include customer analysis, market research, market segmentation, distribution channel policy, product policy and strategy, pricing, advertising, and sales force management. The course stresses oral and written expression and makes use of several computer exercises, spreadsheet analysis, and management simulations.

    Prerequisites

    Permission of instructor

    Notes

    Cannot be used to satisfy any A.B. degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Mon/Wed/Fri 10:00-11:20 AM
    Location:

    Cummings 100

    Instructors:

    Tuck Faculty


  • ENGM 182
    Data Analytics

    Description

    This course provides a hands-on introduction to the concepts, methods and processes of business analytics. Students learn how to obtain and draw business inferences from data by asking the right questions and using the appropriate tools. Topics include data preparation, statistical tools, data mining, visualization, and the overall process of using analytics to solve business problems. Students work with real-world business data and analytics software. Where possible, cases are used to motivate the topic being covered. Students acquire a working knowledge of the “R” language and environment for statistical computing and graphics. Prior experience with “R” is not necessary, but students should have a basic familiarity with statistics, probability, and be comfortable with basic data manipulation in Excel spreadsheets.

    Prerequisites

    ENGS 93 or equivalent, or permission of the instructor.

    Cross Listed Courses

    ENGG 182

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 3A
    Location:

    MACLEAN B01 ZALESK

    Instructors:

    Erin N. Mayfield


    Term: Winter 2024
    Time: M/W 9:00 - 10:50am
    Location: –
    Instructors:

    Erin N. Mayfield


  • ENGG 182
    Data Analytics

    Description

    This course provides a hands-on introduction to the concepts, methods and processes of business analytics. Students learn how to obtain and draw business inferences from data by asking the right questions and using the appropriate tools. Topics include data preparation, statistical tools, data mining, visualization, and the overall process of using analytics to solve business problems. Students work with real-world business data and analytics software. Where possible, cases are used to motivate the topic being covered. Students acquire a working knowledge of the “R” language and environment for statistical computing and graphics. Prior experience with “R” is not necessary, but students should have a basic familiarity with statistics, probability, and be comfortable with basic data manipulation in Excel spreadsheets.

    Prerequisites

    ENGS 93 or equivalent, or permission of the instructor.

    Cross Listed Courses

    ENGM 182

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: M/W 9:00 - 10:50am
    Location:

    MacLean B01 Zaleski

    Instructors:

    Erin N. Mayfield


  • ENGM 183
    Operations Management

    Description

    This course provides an introduction to the concepts and analytic methods that are useful in understanding the management of a firm's operations. We will introduce job shops, assembly lines, and continuous processes. Other topics include operations strategy, aggregate planning, production scheduling, inventory control, and new manufacturing technologies and operating practices.

    Prerequisites

    ENGS 93

    Notes

    Cannot be used to satisfy any A.B. degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location:

    CUMMINGS 100

    Instructors:

    Tuck Faculty


    Term: Winter 2024
    Time: F 9:00-10:30am & 11:00am-12:30pm
    Location:

    Stoneman (Tuck)

    Instructors:

    Laurens G. Debo


  • ENGM 184
    Introduction to Optimization Methods

    Description

    An introduction to various methods of optimization and their use in problem solving. Students will learn to formulate and analyze optimization problems and apply optimization techniques in addition to learning the basic mathematical principles on which these techniques are based. Topic coverage includes linear, nonlinear, and dynamic programming, and combinatorial optimization.

    Prerequisites

    No Prerequisite

    Cross Listed Courses

    ENGG 184

    Notes

    Cannot be used to satisfy any A.B. degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Wed 1:00-2:50 PM, Fri 11:30 AM-1:20 PM
    Location:

    ECSC 008

    Instructors:

    Eric S. Bish


    Term: Fall 2024
    Time: Arrange
    Location: –
    Instructors:

    Eric S. Bish


  • ENGG 184
    Introduction to Optimization Methods

    Description

    An introduction to various methods of optimization and their use in problem solving. Students will learn to formulate and analyze optimization problems and apply optimization techniques in addition to learning the basic mathematical principles on which these techniques are based. Topic coverage includes linear, nonlinear, and dynamic programming, and combinatorial optimization.

    Prerequisites

    No Prerequisite

    Cross Listed Courses

    ENGM 184

    Notes

    Cannot be used to satisfy any A.B. degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Wed 1:00-2:50 PM, Fri 11:30 AM-1:20 PM
    Location:

    ECSC 008

    Instructors:

    Eric S. Bish


  • ENGM 185
    Topics in Manufacturing Design and Processes

    Description

    The course will consist of four main topics: 1) technical estimating, 2) design of experiments, 3) design for manufacturability, 4) statistical process control. We will review technical estimating (TE), a vital skill in today's rapidly changing industry. Illustrative and interesting examples will be used to hone TE techniques. Design of experiments (DOE) will be covered in detail using Montgomery's Design and Analysis of Experiments. Analysis of variance, model adequacy checking, factorial designs, blocking and confounding, regression models, nesting, and fractional factorial and Taguchi designs will be taught. Design for manufacturability (DFM) will be covered so that by the end of the course the student will know how to establish a successful DFM program to optimize and continuously improve designs and manufacturing processes. Cost estimating related to manufacturing processes will also be presented, followed by an overview of failure analysis techniques. The course will also introduce the basics of statistical process control, including the Shewhart Rules.

    Prerequisites

    ENGS 93

    Notes

    Cannot be used to satisfy any A.B. degree requirements
  • ENGM 186
    Technology Project Management

    Description

    Project management focuses on planning and organizing as well as directing and controlling resources for a relatively short-term project effort which is established to meet specific goals and objectives. Project management is simultaneously behavioral, and quantitative, and systematic. The course covers topics in planning, scheduling and controlling projects such as in new product development, technology installation, and construction. This course is aimed at both business and engineering students and combines reading and case-oriented activities.

    Prerequisites

    ENGM 184 or equivalent

    Notes

    Cannot be used to satisfy any A.B. degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 10A
    Location:

    CUMMINGS 200

    Instructors:

    Eric S. Bish


    Term: Winter 2024
    Time: 3A
    Location:

    Cummings 202

    Instructors:

    Eric S. Bish


  • ENGM 187
    Technology Innovation and Entrepreneurship

    Description

    Innovation is the process of translating a new invention or discovery into a commercial product. In this course, some of the guiding principles in technology innovation and entrepreneurship are discussed. The principles encompass intellectual property including patents, product definition including minimal viable product and whole product, customer definition and focus, product development, marketing and sales and communication, and manufacturing. Financial modelling and funding sources are addressed. Leadership practices including hiring, team building, employees, outsourcing and working with investors are also discussed. Students will prepare papers on various topics, make presentations, and create a real or hypothetical business plan as part of the coursework.

    Prerequisites

    No Prerequisite

    Notes

    Cannot be used to satisfy any A.B. degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 2A
    Location:

    MACLEAN 132

    Instructors:

    Ronald C. Lasky


    Term: Winter 2024
    Time: 2A
    Location:

    MacLean 132

    Instructors:

    Ronald C. Lasky


  • ENGM 188
    Law for Technology and Entrepreneurship

    Description

    The solutions to many of the challenges of entrepreneurship in general, and to those of starting up a technologically based business in particular, are provided by the law. A grounding in the law of intellectual property, contractual transactions, business structures, debt and equity finance, and securities regulation, both in the U.S. and in an international context, will help inventors and entrepreneurs to manage this part of the process intelligently and with a high likelihood of success.

    Prerequisites

    No Prerequisite

    Notes

    Cannot be used to satisfy any A.B. degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: M/Tu 8:30AM-10:00AM
    Location:

    Cummings 200

    Instructors:

    Oliver Goodenough


  • ENGM 189.10
    Medical Device Commercialization (.5 credit)

    Description

    This course is designed to expose students to the specialized business frameworks and essential tools for successful translation of biomedical technologies from the lab (concept) to the market (clinic) that are needed by medical device innovators and managers. The curriculum is intended to provide an overview of the process used to assess the commercial viability and potential business opportunity for innovative medical devices. Course content is based on the Concept to Clinic: Commercializing Innovation (C3i) Program offered by the NIH. Teams of 2-3 students will work to develop a commercialization plan for an innovative medical device of their choosing or one provided by the course instructors. Weekly lectures on topics ranging from business validation to regulatory strategies to reimbursement approaches will be followed by team presentations that define how each team proposes to navigate these aspects of medical device commercialization.

    Prerequisites

    Graduate standing in engineering or business administration.

    Notes

    ENGM 189.1 runs for the first five weeks of the term offered and follows the Tuck term schedule, beginning the week of September 5 for Fall 2023. It is followed by partner course ENGM 189.2 for the second five weeks of the term offered. Two classes per week, 5 weeks total. This course carries .5 credit. Cannot be used to satisfy any AB degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Mon/Tues 1:15-2:45 PM
    Location:

    ECSC 041

    Instructors:

    Keith D. Paulsen


  • ENGM 189.20
    Medical Device Development (.5 credit)

    Description

    This module of the course is an overview of existing medical devices and discusses methods for development, evaluation, and approval of new medical devices. The course will cover both diagnostic and interventional devices, and cover clinical and pre-clinical testing issues, as well as a discussion of FDA approval processes, funding startups, and cost effectiveness analysis. The course will involve several case studies as examples. For projects, students will work in teams to analyze needs in the medical setting and come up with a plan for a new device, and analyze how best to develop it with a new startup. Two classes per week, 5 weeks total.

    Prerequisites

    Graduate standing in engineering or business administration.

    Notes

    ENGM 189.2 runs for the second five weeks of the term offered, and is preceded by partner course ENGM 189.1 for the first five weeks of the term offered. Two classes per week, 5 weeks total. This course carries .5 credit. Cannot be used to satisfy any AB degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Mon/Tues 1:15-2:45 PM
    Location:

    ECSC 041

    Instructors:

    Keith D. Paulsen


  • ENGM 190
    Platform Design, Management, and Strategy

    Description

    This course is aimed at students, managers, executives, investors, and entrepreneurs interested in creating, managing, or understanding business platforms. Firms such as Amazon, Apple, Facebook, SalesForce, and SAP operate as ecosystems in which third parties add value. Topics include startup, converting existing businesses, openness, network effects, innovation, cannibalization, pricing, governance, and competition. The course will combine rigorous theory with real-world experience. Case studies will emphasize practical approaches and draw from social media, healthcare, entrepreneurship, enterprise software, mobile services, and consumer products to provide foundations and definitions. This course will also demonstrate established economic principles from the literature on industrial organization, two-sided network effects, information asymmetry, agency, pricing, and game theory. A basic background in microeconomics is recommended as a prerequisite. Platforms are economically important and widely observed in modern economies. For example, HMOs match patients and physicians. Real estate and auction networks match buyers and sellers. Airline reservation systems match travelers to airline flights. However, thanks largely to technology, platforms are becoming much more prevalent. New platforms are being developed and traditional businesses are being reconceived as platforms e.g. U.S. Postal Service, newspapers (Huffington Post). Retail electric markets are evolving into platforms that match consumers with specific power producers, allowing them to express their preferences for source of supply. In creating strategies for platform markets, managers have typically relied on assumptions and paradigms that apply to businesses without network effects. As a result, they have made decisions in pricing, supply chains, product design, and strategy that are inappropriate for the economics of their changing industries.

    Prerequisites

    No Prerequisite

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: M 6 - 9 PM
    Location:

    Georgiopoulos (Raether Hall)

    Instructors:

    Geoffrey G. Parker


  • ENGS 190
    Engineering Design Methodology and Project Initiation

    Description

    This course employs a team project to explore elements of the engineering design process as a means of enhancing student ability in problem definition, development and evaluation of creative alternatives, application and methods of technical and economic analysis, identification and application of ethical and legal constraints, client-consultant interaction, and effective presentation of technical information. Engineering design projects are developed from objectives, requirements, and specifications submitted by industry and other organizations and are pursued over the course of two quarters as a team project. A written and oral Pre-Proposal and a Proposal are required for the project during the fall term. A project advisor is required for each design team to help guide the team's efforts. ENGS 190 is the first half of the two-term course sequence (ENGS 190/290) that must be taken consecutively. ENGS 190/290 is the MEng version of 89/90.

    Prerequisites

    ENGS 21; completion of AB or equivalent UG degree; Admission to MENG program; No more than 6 courses remaining in an approved BE program plan (including this capstone sequence (ENGS 190/290)

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 10A
    Location:

    ECSC 008

    Instructors:

    Solomon G. Diamond


    Term: Fall 2023
    Time: 2A
    Location:

    ECSC 116

    Instructors:

    Solomon G. Diamond


  • ENGM 191
    Product Design and Development

    Description

    This class teaches modern tools and methods for product design and development. The cornerstone is a project in which student teams conceive, design, and prototype a physical product. The class is primarily intended for Thayer MEM, MEng, Thayer PhD Innovation, Tuck MBA students, and Dartmouth medical students.

    Prerequisites

    ENGM 183 or Instructor permission.

    Notes

    Cannot be used to satisfy any AB degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: TH 2 - 3:20 PM, F 2 - 3:50 PM
    Location:

    ECSC 008

    Instructors:

    Elizabeth Murnane


  • ENGG 192
    Independent or Group Study in Engineering Sciences

    Description

    An independent study course in lieu of, or supplementary to, a 100-level course, as arranged with a faculty member. To be used in satisfaction of advanced degree requirements, requests for approval must be submitted to the Thayer School graduate program director no later than the end of the first week of classes in the term in which the course is to be taken. No more than one such course should be used in satisfaction of requirements for any degree. Proposed courses should include full syllabus, resources and student evaluation methods. (Cannot be used to satisfy any AB degree requirements. May not be used for term-length design projects.) There may be a small number of remote students, who are part of a designated fully remote MEng program, enrolled in this course.

    Notes

    Cannot be used to satisfy any A.B degree requirements. May not be used for term-length design projects.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Summer 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Fall 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Winter 2024
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2024
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Summer 2024
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Fall 2024
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


  • ENGG 194
    PhD Oral Qualifier

    Description

    The oral qualifying exam, a set of questions put forward by an oral examination committee to the candidate, normally takes place before or during the fifth term of the student's program, or, in exceptional circumstances, early in the sixth term. The exam is open to the faculty, but not to the general public. The committee tests the candidate's knowledge of principles and methods underlying the field in which advanced work is to be performed. The exam covers material selected by the candidate's advisor in consultation with the examining committee, and includes coverage of mathematical techniques appropriate to the research area. The structure of the preparation for the exam is flexible. The examination committee consists of 4 members: the chair plus 3 Dartmouth faculty examiners, with at least 2 of the examiners from Thayer School. A Thayer faculty member other than the student's advisor chairs the committee. This chair is assigned by the director of the M.S. and Ph.D. programs. The examination committee gives the student a pass, fail, or conditional pass result. Students who fail may retake the oral examination — one time only — within the following 3 months. No third attempt is allowed.

    Prerequisites

    Ph.D. student standing

    Notes

    Cannot be used to satisfy any A.B., B.E., M.E.M., or M.S. degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Summer 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Fall 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Winter 2024
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2024
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Summer 2024
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Fall 2024
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


  • ENGG 195
    Seminar on Science - Technology and Society

    Description

    Presentation and discussion of timely issues in scientific and technological development and its relation to society, at the weekly Jones Seminar series, which is every Friday afternoon 3:30pm-4:30pm. Topics vary from week to week, with speakers nominated by the students and faculty of the Engineering School. Topics include scientific developments, technology and impacts of R&D on various aspects of society; ethics, social issues, environmental concerns, and government policy; entrepreneurship, marketing, labor markets, quality, international competition, and legal liability. All enrolled students must attend the weekly Jones Seminar, with allowance for absences due to health or research-related reasons. The credit/no credit grade for this course is based on seminar attendance.

    Prerequisites

    Ph.D. student standing

    Notes

    Cannot be used to satisfy any A.B, B.E., M.E.M., or M.S. degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: F 3:30 - 4:30
    Location:

    CUMMINGS 100

    Instructors:

    Thayer Faculty


    Term: Spring 2023
    Time: F 3:30 - 4:30
    Location:

    CUMMINGS 100

    Instructors:

    Thayer Faculty


    Term: Fall 2023
    Time: F 3:30 - 4:30 PM
    Location:

    Cummings 100

    Instructors:

    Ian Baker


    Term: Winter 2024
    Time: Fri 3:30-4:30 PM
    Location:

    Cummings 100

    Instructors:

    Thayer Faculty


    Term: Spring 2024
    Time: F 3:30-4:30 PM
    Location:

    Cummings 100

    Instructors:

    Thayer Faculty


  • ENGG 197
    Ph.D. Professional Workshops

    Description

    A sequence of workshops on the preparation for professional life after the Ph.D. program, culminating in the completion of a curriculum vitae or resume, outline of possible jobs, and a competitive grant proposal. A major goal is for the student to design and write a grant for a technology startup program or for an academic research grant. Successful research and SBIR proposals are outlined and the processes for evaluating them are offered by research principal investigators, grant administration officials, and corporate representatives. Both academic CVs and industry resumes can be developed. Workshops include job search guides, management skills and research team management. Submitted student proposals and CVs are critiqued for improvement.

    Prerequisites

    Ph.D. student standing

    Notes

    Cannot be used to satisfy any AB, BE, MEM, MEng, or MS degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location:

    ECSC 009

    Instructors:

    Thayer Faculty


    Term: Winter 2024
    Time: W 3:30 - 5:30pm
    Location:

    MacLean 132

    Instructors:

    Allan Bieber


  • ENGG 198
    Research-In-Progress Workshop

    Description

    Annual meeting of all doctoral candidates in residence with each candidate presenting in generally understandable terms his or her research progress over the past year.

    Prerequisites

    Ph.D. student standing

    Notes

    Cannot be used to satisfy any AB, BE, MEM, MEng, or MS degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Ian Baker


    Term: Winter 2024
    Time: Arrange
    Location: –
    Instructors:

    Ian Baker


  • ENGG 199
    Special Topics in Engineering Sciences

    Description

    A special topics lecture course in lieu of, or supplementary to, a 100-level course, as arranged by a faculty member to be used in satisfaction of advanced degree requirements. The course must be approved by the graduate programs committee in advance of the term in which it is offered. No more than two such courses should be used in satisfaction of requirements for any degree. To permit action prior to the term’s end, requests for approval must be submitted to the graduate director no later than the eighth week of the term preceding the term in which the course is to be offered. Proposed courses should include full syllabus, resources, and student evaluation methods. Courses that have a 100-level prerequisite should use ENGG 299.

    Notes

    ENGG 199 - Special Topic courses are offered a maximum of 3 terms as a 199.xx course. Course topics may be added over the course of the academic year. Please check the Term Course Schedules for which courses are scheduled in any upcoming terms. Consult your advisor on how best to include a 199 course in your program plan.
  • ENGG 199.02
    Model Based Systems Engineering

    Description

    This course is designed to introduce students to the world of model-based systems engineering. Systems Engineering is an interdisciplinary field of engineering and engineering management that enables the realization of successful complex systems over their life-cycles. Systems Engineering integrates multiple disciplines and specialty groups into a team effort forming a structured development process that proceeds from concept to production to operation to obsolescence. Systems Engineering considers the technical, social, and business needs of all stakeholders with the goal of realizing a successful system. At its core, systems engineering utilizes systems thinking principles to organize this body of knowledge. This course will prepare students to engineer, analyze, and simulate complex systems. Such systems are characterized by a high level of heterogeneity and a large number of components. They will appreciate the physical, informatic, social and economic aspects of such systems. They will use systems thinking concepts and abstractions to manage complexity. They will learn to use model-based systems engineering techniques to model a system’s form, function, and concept. They will analyze the structure of these systems using graph-theoretic approaches. Finally, they will learn to simulate social, technical, and economic systems with continuous-time and discrete-event dynamics. The systems engineering skills developed over the course are applicable to a broad range of disciplinary applications.
    Design Credit

    Prerequisites

    ENGG 199, like other introductory graduate-level systems engineering courses at other universities, is meant to be taken after the student has well established their undergraduate engineering program.
  • ENGG 199.03
    High-Frequency Power Magnetics Design

    Description

    One of the fundamental advantages of power electronics is the ability to use high frequencies which enable reductions in physical size, weight and cost of passive components such as magnetics with losses also reduced. However high-frequency effects in both magnetic cores and in windings rapidly increase power losses at higher frequencies limiting performance and inhibiting the use of increased frequency to yield further improvements. After a review of magnetics modeling and design fundamentals, the class will examine best-practice techniques for high-frequency magnetics modeling and design. Selected recent and current research in modeling, design, and fabrication will be examined in detail, including self-resonant passive components. Finally, applications to wireless power transfer will be studied.
  • ENGG 199.05
    Introduction to Computational Materials Science and Engineering

    Description

    Computational modeling in materials science is a powerful tool that allows discovery of new materials and exploration of materials theory. This course introduces the use of computational modeling to understand and predict materials behavior, properties and processes. The course will introduce a series of common materials modeling approaches from molecular dynamics to Monte-Carlo simulations and Density Functional Theory. All methods will be illustrated using use cases from various fields of materials science (e.g., Li-ion batteries, structural alloys, …). The students will learn to apply these methods hands-on on specific problems writing code and using open-source codes. A strong emphasis will be on the critical assessment of the limits of the models.

    Prerequisites

    ENGS 24, ENGS 20, and working knowledge of ordinary PDE's. Students not meeting the prerequisites and non-engineering majors may seek permission.
  • ENGG 199.06
    Flexible Electronics-Matl Dsgn for Energy, Sensing, and Display

    Description

    Flexible electronics make up an emerging class of devices that can tackle technological challenges for which traditional rigid systems are unsuitable—for example, lightweight wearable sensors for health applications or low-cost solar energy. This course will develop a multidisciplinary understanding of how to engineer thin film materials with unique optoelectronic and electronic functionality for flexible devices within a set of constraints imposed by thin film mechanics. This will include a study of electronic devices such as thin film solar cells, light emitting diodes, and thin film transistors as well as the large area deposition methods used to pattern and integrate these systems. Knowledge from this course is relevant preparation for careers in the display industry ($100 bil.) and flexible electronics industry ($50 bil.).

    Prerequisites

    ENGS 24 and at least one of (ENGS 32, 60, 122, 131, 134, 135)

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: 10A
    Location:

    ECSC 041

    Instructors:

    William J. Scheideler


  • ENGG 199.07
    Introduction to Bioelectronics

    Description

    In this course, the fundamentals and applications of micro-and nano-technology-based bioelectronics are introduced. Topics include bioelectricity, biosensor basics, bioelectronic device fabrication, integrated circuit packaging, and in-depth discussions on biopotential electrodes for the recording and stimulation of bioelectricity. Medical device regulations will also be introduced together with safety and ethical issues as critical considerations towards biomedical device translation and commercialization. The course emphasizes the design and analysis methods in developing new bioelectronics. The course project is designed for students to gain experiences and insights in utilizing what’s learned in this course to conduct in-depth critical reviews of recent bioelectronic developments.

    Prerequisites

    ENGS 22; CHEM 6, or graduate standing

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 11
    Location:

    MacLean 201

    Instructors:

    Hui Fang


  • ENGG 199.08
    Post-Modern and Non-Linear Control

    Description

    This course provides an in-depth overview of several post-modern and non-linear control concepts and methods that are applicable to a wide range of deterministic and stochastic dynamical systems. The following topics are covered in the course: review of state estimation and modern control theory, mathematical models, input-state and input-output feedback linearization, iterative learning control, evolutionary algorithms, artificial neural networks, dynamic programming, model predictive control, reinforcement learning, and relationship of reinforcement learning to model predictive control and optimal control.

    Prerequisites

    ENGS 26; ENGS 145 is recommended
  • ENGG 199.10
    Master of Engineering Design Project Initiation

    Description

    This course is the start of a two course sequence intended to develop and practice the skills of engineering project management while engaging in an advanced engineering project. The course will provide students with skills and hands-on experience that will benefit them as they embark on professional careers. Students will learn tools for project leadership including: development of schedules and budgets, risk identification and mitigation, communication skills, personnel management, and design practices for both hardware and software. The Instructor will draw heavily from personal experience and that of guest lecturers who are practicing engineers in a variety of disciplines and industries. Students will practice these skills by working as part of a team tasked with an industry-sponsored, real-world engineering project. The engineering teams will be responsible for all aspects of the project including: work plan definition, technical execution, risk identification and mitigation, utilization of outside resources, schedule and budget management, and client interactions.

    Prerequisites

    Successful application

    Notes

    This course will not be offered in 2024-25.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: 2A
    Location:

    ECSC B01

    Instructors:

    David B. Kynor


    Term: Winter 2024
    Time: 2A
    Location:

    ECSC 042

    Instructors:

    David B. Kynor


  • ENGG 199.11
    Master of Engineering Design Project Completion

    Description

    This course is a follow-on to the winter term of ENGG 199.10 - MEng Design Project Initiation. This course is focused on completion of the engineering project that was initiated during the Winter Term. The course will provide students with skills and hands-on experience that will benefit them as they embark on professional careers. Students will put into practice the project execution and leadership skills introduced in the classroom during ENGG199.10. These skills include: schedule development, budget development and monitoring, risk identification and mitigation, communication skills, personnel management, client interaction, hardware and software design practices, and preparation and delivery of client demonstrations and presentations. Students will lead and be part of a project team tasked with executing an industry-sponsored, real-world engineering project. The engineering teams will be responsible for all aspects of the project including: work plan definition, technical execution, risk identification and mitigation, utilization of outside resources, schedule and budget management, and client interactions.

    Prerequisites

    ENGG 199.10

    Notes

    This course will not be offered in 2024-25.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 2A
    Location:

    ECSC B01

    Instructors:

    David B. Kynor


    Term: Spring 2024
    Time: 2A
    Location:

    ECSC 041

    Instructors:

    David B. Kynor


  • ENGG 199.12
    Geophysical Fluid Dynamics

    Description

    Geophysical Fluid Dynamics is the study of planetary flows in the atmosphere and ocean basins. It underpins the study of climate dynamics. After a review of the physics of mass, momentum, and energy balances within approximations suitable to planetary flows, and exposition of the effect of planetary rotation (the Coriolis effect), the course continues with the study of boundary layers, waves, instabilities, mixing and turbulence in their planetary manifestations. These concepts are then utilized to study the general oceanic and atmospheric circulations, heat transfer at the hemispheric scale, and climate-affecting large-scale oscillations such as the North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), and the El Niño/Southern Oscillation (ENSO). It concludes with specific topics related to sea-ice interactions.

    Prerequisites

    ENGS 034 or permission of instructor
  • ENGG 199.13
    Numerical Modeling of Glacier and Ice Sheet Dynamics

    Description

    This course explores the physics and dynamics of glaciers and ice sheets. Course content includes glacier mass balance, the material properties and rheology of ice, the basic equations of ice-sheet and -shelf flow, basal processes, calving processes, the stability and history of ice sheets. These topics will be approached using mathematical physics, geophysical data, simple computer simulations, and large-scale ice sheet models. We also introduce the students to numerical methods for modeling glaciers, including the finite-element method and provide some elements of inverse problem theory. 
    Includes Lab

    Prerequisites

    ENGS 23 or MATH 23; and ENGS 33

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 2A
    Location:

    ECSC 041

    Instructors:

    Helene Seroussi


  • ENGG 199.14
    High Frequency and Switching Electronic Circuits

    Description

    High-frequency circuits that rely on switching processes are pervasive in modern electronic systems – from computing and communications to consumer electronics, biomedical circuits, and renewable energy. While most courses teach analog (linearized small signal) or digital (binary logic) perspectives, it is increasingly important to understand the modelling and use cases for large-signal switched-mode operation of modern complementary metal-oxide semiconductor (CMOS) transistors and circuits. This class will provide a unified perspective on switched-mode circuit operation that can be used across a wide range of electronic disciplines from high-speed digital CMOS design to basic radio-frequency (RF) wireless circuits, data conversion, and power management circuit blocks. Transistor-level circuit models will consider the unique properties of switching devices to develop a unified perspective that can be applied in a wide range of circuit design disciplines. Cadence IC design tools will be used to extract model parameters from devices in a real semiconductor foundry process design kit (PDK). These models will be used to design and optimize digital logic blocks using a ‘logical effort’ framework, high-frequency DC-DC converters based on conventional buck-boost, switched capacitor (SC), and hybrid-resonant switched-capacitor converters, and radio frequency power amplifiers (RF PAs) for modern wireless standards.

    Prerequisites

    ENGS 61 and one of ENGS 125 or ENGS 126 (or instructor permission)

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: 10
    Location:

    ECSC 009

    Instructors:

    Jason T. Stauth


  • ENGS 200
    Methods in Applied Mathematics II

    Description

    Continuation of ENGS 100 with emphasis on variational calculus, integral equations, and asymptotic and perturbation methods for integrals and differential equations. Selected topics include functional differentiation, Hamilton's principles, Rayleigh-Ritz method, Fredholm and Volterra equations, integral in transforms, Schmidt-Hilbert theory, asymptotic series, methods of steepest descent and stationary phase, boundary layer theory, WKB methods, and multiple-scale theory.

    Prerequisites

    ENGS 100, or equivalent

    Cross Listed Courses

    PHYS 110

    Notes

    Not offered 2021-2023
  • ENGS 202
    Nonlinear Systems

    Description

    The course provides basic tools for modeling, design, and stability analysis of nonlinear systems that arise in a wide range of engineering and scientific applications including robotics, autonomous vehicles, mechanical and aerospace systems, nonlinear oscillators, chaotic systems, population genetics, learning systems, and networked complex systems. There are fundamental differences between the behavior of linear and nonlinear systems. Lyapunov functions are powerful tools in dealing with design and stability analysis of nonlinear systems. After addressing the basic differences between linear and nonlinear systems, the course will primarily focus on normal forms of nonlinear systems and Lyapunov-based control design methods for a variety of applications with an emphasis on robotics, mechanical control systems, and particle systems in potential fields.

    Prerequisites

    ENGS 100 and ENGS 145 or equivalents and familiarity with MATLAB

    Notes

    Not offered 2021-2023
  • ENGM 204
    Data Analytics Project Lab

    Description

    The widespread proliferation of IT-mediated economic activity generates an abundance of micro-level data about markets as well as consumer, supplier, and competitor preferences. This has led to the emergence of a new form of competition based on the extensive use of analytics, experimentation, and fact-based decision-making. In nearly every industry the competitive strategies organizations are employing today rely extensively on data analysis to predict the consequences of alternative courses of action, and to guide executive decision-making. The purpose of the Data Analytics Project Lab (DAPL) course is to provide a background on how data analytics, machine learning and artificial intelligence create value for organizations. Lectures on recent trends and tutorials on current AI/ML techniques will be complemented by a major team project. The course will match student teams with projects involving analytics and machine learning as they apply to business questions and problems. Projects will be sourced from commercial and government organizations. Instructor approval of student sourced projects will be considered on a case-by-case basis.

    Prerequisites

    ENGM 182, ENGS 108, COSC 274, or instructor approval (demonstrated background in data analytics with R, Python, or similar software)

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: M/T 10:20 - 11:50
    Location:

    MURDGH STONEMAN

    Instructors:

    Geoffrey G. Parker


    Term: Spring 2024
    Time: M/T 1:30 - 3:00pm
    Location: –
    Instructors:

    Geoffrey G. Parker

    Sam Raymond


  • ENGS 205
    Computational Methods for Partial Differential Equations II

    Description

    Boundary element and spectral methods are examined within the numerical analysis framework established in ENGS 105. The boundary element method is introduced in the context of linear elliptic problems arising in heat and mass transfer, solid mechanics, and electricity and magnetism. Coupling with domain integral methods, e.g., finite elements, is achieved through the natural boundary conditions. Extensions to nonlinear and time-dependent problems are explored. Spectral methods are introduced and their distinctive properties explored in the context of orthogonal bases for linear, time-invariant problems. Extension to nonlinear problems is discussed in the context of fluid mechanics applications. Harmonic decomposition of the time-domain is examined for nonlinear Helmholtz-type problems associated with E&M and physical oceanography.

    Prerequisites

    ENGS 105

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: Arrange
    Location: –
    Instructors:

    Keith D. Paulsen


  • ENGG 210
    Spectral Analysis

    Description

    An advanced treatment of digital signal processing for the analysis of time series. A study is made of parametric and nonparametric methods for spectral analysis. The course includes a review of probability theory, statistical inference, and the discrete Fourier Transform. Techniques are presented for the digital processing of random signals for the estimation of power spectra and coherency. Examples are taken from linear system theory and remote sensing using radar. Laboratory exercises will be assigned requiring the use of the computer.

    Prerequisites

    ENGS 110

    Notes

    Can be used by undergraduates for A.B. course count only. Not offered 2021-2023
  • ENGG 212
    Communications Theory

    Description

    An advanced treatment of communications system engineering with an emphasis on digital signal transmission. The course includes a review of probability theory, random processes, modulation, and signal detection. Consideration will be given to channel modeling, the design of optimum receivers, and the use of coding.

    Prerequisites

    ENGS 110

    Notes

    Can be used by undergraduates for A.B. course count only. Not offered 2021-2023
  • ENGS 220
    Electromagnetic Wave Theory

    Description

    Continuation of ENGS 120, with emphasis on fundamentals of propagation and radiation of electromagnetic waves and their interaction with material boundaries. Selected topics include propagation in homogeneous and inhomogeneous media, including anisotropic media; reflection, transmission, guidance and resonance; radiation fields and antennas; diffraction theory; and scattering.

    Prerequisites

    ENGS 100 and ENGS 120 or permission of the instructor
  • ENGG 230
    Fatigue and Fracture

    Description

    A study of the fracture and fatigue behavior of a wide range of engineering materials (metals, ceramics, polymers, biological materials, and composites). Topics include work of fracture, fracture mechanics (linear elastic, elastic-plastic and plastic), fracture toughness measurements, crack stability, slow crack growth, environmentally assisted cracking, fatigue phenomenology, the Paris Law and derivatives, crack closure, residual stress effects, and random loading effects. These topics will be presented in the context of designing to avoid fracture and fatigue.

    Prerequisites

    ENGS 130 or permission of instructor

    Notes

    Can be used by undergraduates for A.B. course count only

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: Arrange
    Location:

    CUMMINGS 102

    Instructors:

    Yan Li


    Term: Spring 2024
    Time: M/W 12:50 - 2:40pm
    Location:

    Cummings 102

    Instructors:

    Yan Li


  • ENGS 250
    Turbulence in Fluids

    Description

    An introduction to the statistical theory of turbulence for students interested in research in turbulence or geophysical fluid dynamics. Topics to be covered include the statistical properties of turbulence; kinematics of homogeneous turbulence, phenomenological theories of turbulence; waves, instabilities, chaos and the transition to turbulence; analytic theories and the closure problem; diffusion of passive scalars; and convective transport.

    Prerequisites

    ENGS 150 or equivalent

    Notes

    Not offered 2021-2023
  • ENGG 260
    Advances in Biotechnology

    Description

    Biotechnology continues to undergo explosive and transformative growth. Our fundamental knowledge of biological systems, which underlies modern biotechnology, is now being updated and revised on a daily basis. Likewise, instrumentation and biological tools are experiencing a continuous revolution that pushes the boundaries of applied biology. To be competitive within their professions, biotechnologists and biological engineers must therefore maintain broad knowledge of current advances in fields related to their areas of specialization. This course will survey current peer-reviewed literature from a variety of sources and help students develop good reading habits, literature search skills, and the ability to critically assess peer-reviewed literature.

    Prerequisites

    Graduate standing and ENGS 160 or ENGS 163

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location:

    MACLEAN 201 RETTS

    Instructors:

    Margaret E. Ackerman

    Karl E. Griswold


    Term: Spring 2023
    Time: T 8:30 -10
    Location:

    ECSC B01

    Instructors:

    Margaret E. Ackerman

    Karl E. Griswold


    Term: Fall 2023
    Time: Tues 8:30-10:00 AM
    Location:

    MacLean 201

    Instructors:

    Margaret E. Ackerman

    Thayer Faculty


    Term: Winter 2024
    Time: T 8:30-10:00am
    Location:

    MacLean 201

    Instructors:

    Margaret E. Ackerman

    Thayer Faculty


    Term: Spring 2024
    Time: T 8:30-10:00 AM
    Location:

    ECSC B01

    Instructors:

    Margaret E. Ackerman


  • ENGG 261
    Biofuels and Bioenergy

    Description

    Bioenergy technologies will be surveyed, including feedstocks, bioelectricity production, biofuel production, and conversion technologies. Fermentation-derived biofuels will then be considered in more detail including first, and second, generation biofuels as well as the fundamentals of microbial cellulose utilization. Consolidated bioprocessing will be examined with respect to feedstock solubilization, metabolic engineering, technoeconomic analysis, and research frontiers. Sustainability tools will be introduced and assessments discussed. The course will feature readings from the literature, guest lectures by field leaders, and student projects.

    Prerequisites

    ENGS 157 and ENGS 161 and permission of instructor

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: 10A
    Location:

    Cummings 102

    Instructors:

    Lee R. Lynd


  • ENGS 262
    Advanced Biological Circuit Engineering

    Description

    This course will provide advanced techniques for the design, modeling, and experimental implementation of complex synthetic biological circuits including feedback control and regulation. Advanced & complex synthetic circuits will be designed and tested in bacteria in the laboratory. Computer aided design, modeling, and simulation will use CADENCE, an industry standard electronic circuit design tool. Applications of synthetic biology to medicine and biotechnology will be discussed. In addition, the students will be expected to design a synthetic biological circuit with feedback and control techniques for a class project.

    Prerequisites

    ENGS 162 (Basic Biological Circuit Engineering); OR Equivalent experience in Molecular Biology Techniques (Either ENGS 35, BIOL 45, BIOL 46) AND equivalent experience in Signals and System Modeling (e.g. ENGS 22).

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: 2
    Location:

    CUMMINGS 105

    Instructors:

    Rahul Sarpeshkar


    Term: Spring 2024
    Time: 2
    Location:

    Cummings 105

    Instructors:

    Rahul Sarpeshkar


  • ENGG 269
    Advances in Biomedical Engineering

    Description

    The field of biomedical engineering (BME) is expansive and growing, with expertise areas in each of 1) imaging and medical physics; 2) biomaterials & biomechanics, 3) devices and interventions; and 4) molecular and cellular engineering, and this journal club class will focus on one of these areas or a combination of them as designed each term.  Our fundamental knowledge of systems and methods that form this evolution are being updated and revised on a daily basis, through academic research. The engineering and applied science aspects of these areas are published in scholarly journals and conference proceedings, and the fundamental discoveries and advances need to be understood. To be competitive within their professions, biomedical engineers must therefore maintain broad knowledge of current advances in fields related to their areas of specialization. This course will survey current peer-reviewed literature from a variety of sources and help students develop good reading habits, literature search skills, and the ability to critically assess peer-reviewed literature.  The topic of each term will vary with the students enrolled, and several BME offerings with slightly different topic focus may occur.  PhD students are expected to take this course each term of their first year, ideally, and receive a total of one course credit.

    Prerequisites

    PhD standing

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: T 1010 - 12
    Location:

    MACLEAN 201 RETTS

    Instructors:

    Jonathan T. Elliott


    Term: Spring 2023
    Time: Arrange
    Location:

    CUMMINGS 105

    Instructors:

    Jonathan T. Elliott


    Term: Fall 2023
    Time: Arrange
    Location:

    TBD

    Instructors:

    Jonathan T. Elliott


    Term: Winter 2024
    Time: Arrange
    Location: –
    Instructors:

    Jonathan T. Elliott


    Term: Spring 2024
    Time: Arrange
    Location: –
    Instructors:

    Jonathan T. Elliott


  • ENGS 290
    Engineering Design Methodology and Project Completion

    Description

    This course is the second unit in the two-course team engineering design sequence ENGS 190/290. The objective of the course is to develop the students' professional abilities by providing a realistic project experience in engineering analysis, design, and development. Students continue with the design teams formed in ENGS 190 to complete their projects. Design teams are responsible for all aspects of their respective projects: science, innovation, analysis, experimentation, economic decisions and business operations, planning of projects, patents, and relationships with clients. ENGS 290 is the MEng version of ENGS 90.

    Prerequisites

    Successful completion of ENGS 190

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2024
    Time: 3A
    Location:

    Cummings 100

    Instructors:

    Solomon G. Diamond


  • ENGG 295
    Supervised Teaching

    Description

    Students enrolled in this course will work closely with a faculty member to provide assistance in teaching an engineering course. Students are expected to devote twenty hours per week to one or more of the following activities: developing assignments, preparing and delivering material (e.g., a lecture, in-class activity, discussion) for one or more class hours, organizing and delivering tutorials or problem sessions, laboratory instruction, evaluating student responses, and grading. Students will also concurrently attend a multi-part workshop to learn about pedagogy and develop their teaching skills. Performance will be monitored throughout the term by the supervising faculty member and/or laboratory instructor, and feedback will be provided on teaching effectiveness. Students interested in pursuing an academic career are strongly encouraged to enroll. This course can only be taken once, and is offered on a credit/no credit basis.

    Prerequisites

    PhD student standing

    Notes

    Normally, students will elect this course in a term subsequent to passing the qualifying examination. No additional compensation will be provided for the TA activity.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2023
    Time: –
    Location: –
    Instructors:

    Thayer Faculty


    Term: Summer 2023
    Time: –
    Location: –
    Instructors:

    Thayer Faculty


    Term: Fall 2023
    Time: –
    Location: –
    Instructors:

    Thayer Faculty


    Term: Winter 2024
    Time: –
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2024
    Time: –
    Location: –
    Instructors:

    Thayer Faculty


  • ENGG 296
    Graduate Research 1

    Description

    Graduate research (1 credit) For M.S. and Ph.D. students

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2023
    Time: –
    Location: –
    Instructors:

    Thayer Faculty


    Term: Summer 2023
    Time: –
    Location: –
    –

    Term: Fall 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Winter 2024
    Time: –
    Location: –
    –

    Term: Spring 2024
    Time: –
    Location: –
    –

    Term: Summer 2024
    Time: –
    Location: –
    –

  • ENGG 297
    Graduate Research 2

    Description

    Graduate research (2 credits) For M.S. and Ph.D. students

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2023
    Time: –
    Location: –
    Instructors:

    Thayer Faculty


    Term: Summer 2023
    Time: –
    Location: –
    –

    Term: Fall 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Winter 2024
    Time: –
    Location: –
    –

    Term: Spring 2024
    Time: –
    Location: –
    –

    Term: Summer 2024
    Time: –
    Location: –
    –

  • ENGG 298
    Graduate Research 3

    Description

    Graduate research (3 credits) For M.S. and Ph.D. students

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Spring 2023
    Time: –
    Location: –
    Instructors:

    Thayer Faculty


    Term: Summer 2023
    Time: –
    Location: –
    –

    Term: Fall 2023
    Time: Arrange
    Location: –
    Instructors:

    Thayer Faculty


    Term: Winter 2024
    Time: –
    Location: –
    –

    Term: Spring 2024
    Time: –
    Location: –
    –

    Term: Summer 2024
    Time: –
    Location: –
    –

  • ENGG 299
    Advanced Special Topics in Engineering Sciences

    Description

    A special topics course in lieu of, or supplementary to, a 200-level course, as arranged by a faculty member, to be used in satisfaction of degree requirements. The course must be approved by the graduate programs committee in advance of the term in which it is offered. No more than one such course may be used in satisfaction of requirements for any degree. Requests for approval must be submitted to the program director no later than the eighth week of the term preceding the term in which the course is to be offered, to permit action prior to the term's end. Proposed courses should include full syllabus, resources and student evaluation methods. Courses that do not have a 100-level prerequisite should use ENGG 199.

    Notes

    Cannot be used to satisfy any A.B. degree requirements
  • ENGG 300
    Enterprise Experience Project

    Description

    Hands-on experience with existing enterprises can create a valuable training and enrichment experience for students in the Thayer graduate programs. At the end of the internship, you will make a presentation to the Thayer community that addresses the nature of the enterprise you were engaged in, the problem you were assigned, and the results and impact of your project. The purpose of the presentation is to share lessons learned from the experience with the Thayer community. The presentation will be accompanied by a short but complete written report. Neither the presentation nor report should contain confidential information of the enterprise. The course is graded on a credit/no credit basis by the instructor after completion of the report. Students may enroll in an outside internship program with the support of their faculty advisor, as long as they maintain enrollment in their program or take an approved leave of absence. Students holding F-1 visa status will need to get an updated I-20 endorsed with employment authorization, prior to starting their internship. F-1 students should consult the Office of Visa and Immigration Services (OVIS) about the application process. Internships normally occur in the summer terms, are paid by the company, and should coincide with the start and end of the term. Students electing to do an internship and who are not taking a leave of absence must enroll in ENGG 300 to formalize their internship experience, complete an Internship proposal form (available in the Thayer Registrar’s Office), and meet with the instructor prior to enrollment. During the internship a student is not generally funded by a stipend and the tuition and health insurance (if applicable) is funded through Thayer scholarship. Students in the PhD Innovation program should consult the policy & requirements for that program.

    Prerequisites

    Enrollment is open to MS and PhD students that have completed at least three (3) quarters of program residency. Students may enroll in the course more than once, but students holding F-1 visas should consult with OVIS.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: Arrange
    Location:

    Individualized Study

    Instructors:

    Charles E. Wyman


    Term: Summer 2023
    Time: Arrange
    Location:

    Individualized Study

    Instructors:

    Charles E. Wyman


    Term: Fall 2023
    Time: Arrange
    Location: –
    Instructors:

    Ronald C. Lasky


    Term: Winter 2024
    Time: Arrange
    Location: –
    Instructors:

    Ronald C. Lasky


    Term: Summer 2024
    Time: Arrange
    Location: –
    Instructors:

    Ronald C. Lasky


  • ENGG 309
    Topics in Computational Science

    Description

    Contemporary theory and practice in advanced scientific computation, organized by physical application area. Course comprises two 5-week modules, selected from the following: Computational Fluid Dynamics: This module covers four basic contemporary issues: (i) the inherent nonlinearity of fluids; (ii) the mixed hyperbolic/elliptic nature of the differential equations governing fluid motion; (iii) the concomitant algorithmic complexity of their numerical treatment; and (iv) the size, i.e., the large number of degrees of freedom found in most realistic problems. Discussion of advection-dominated flows: physical and numerical properties; temporal and spatial discretization issues; method of characteristics, upwinding, Galerkin and Petrov-Galerkin methods; artificial viscosity. Navier-Stokes and shallow water equations in 2- and 3-D: mixed interpolation; primitive equation and higher-order formulation; staggered meshes; boundary conditions on pressure, transport and stress; radiation conditions. Frequency domain solution of hyperbolic problems: nonlinear generation of harmonics; truncation errors in iterative methods. Prerequisites: ENGS 34 and ENGS 105, or equivalent Instructor: Staff Computational Solid Mechanics: This module will deal with the development and application of finite element methods for solid mechanics problems. After a brief treatment of the theory of elasticity, the finite element equations for elastic solids will be developed using variational techniques. Applications in two- and three-dimensional static elasticity will be considered. Techniques will then be developed to analyze the following classes of problems; nonlinear material behavior, especially plasticity; plates and shells; problems involving contact between two bodies; and dynamic analysis of elastic bodies. Prerequisites: ENGS 33 and ENGS 105, or equivalent Instructor: Staff Computational Electromagnetics: This module focuses on numerical solutions of the Maxwell equations. Emphasis will be placed on problem formulation and implementation issues. Examples will be selected from a broad spectrum of topics such as electromagnetic scattering, waveguides, microwave circuits and strip-lines, bioelectromagnetics. Development of software to solve representative problems will be required. It is anticipated that the student will be capable of reading and understanding the current computational electromagnetics literature upon completion of this course. Prerequisites: ENGS 105 and ENGS 120 Instructor: Staff
  • ENGG 310
    Advanced Topics in Signals and Systems

    Description

    Advanced study in signal processing and system theory. Possible topics include multi-input/multi-output systems, two-dimensional systems (image processing), modeling and identification, optimal filtering, and advanced optics. Readings in current research literature and student presentations.

    Prerequisites

    Different for each topic; normally include ENGS 123 and ENGG 210 or equivalent, and permission of instructor

    Notes

    Cannot be used to satisfy any A.B. degree requirements
  • ENGG 312
    Topics in Statistical Communication Theory

    Description

    Advanced study in any of the following or other topics may be pursued: information theory, coding, noise, random signals, extraction of signals from noise, pattern recognition, and modulation theory. Normally offered in alternate years.

    Prerequisites

    ENGS 93, ENGS 110, and permission of instructor

    Notes

    Cannot be used to satisfy any A.B. degree requirements
  • ENGG 317
    Topics in Digital Computer Design

    Description

    Critical analysis of current literature in an emerging area of digital technology, such as multi-processor architecture, decentralized networks of small computers, bubble memories, ultra-fast arithmetic logic, specialized computers for digital filtering, etc. A term paper will be required.

    Prerequisites

    ENGS 116 and permission of instructor

    Notes

    Cannot be used to satisfy any A.B. degree requirements
  • ENGG 321
    Advanced Innovation and Entrepreneurship

    Description

    ENGG 321 is the capstone course of the PhD Innovation Programs and provides students with knowledge about the process of commercializing a new technology. During the winter term, students meet on a weekly basis to discuss a variety of reading assignments in innovation and enterprise building. During the spring term, students choose a technology to commercialize, preferably from their own dissertation research efforts. During that term students develop a full enterprise plan for commercialization of the technology, including IP issues and strategy, applications, market forecasting and strategy, product development plans, a full multi-year monthly financial cost plan for all aspects of the enterprise, and a resource plan including personnel and funding. Students meet weekly and make installment presentations to their classmates and instructor for discussion and modification. Ad hoc discussion of related issues to running an enterprise, such as team building and personnel, infrastructure, funding options, whole product, and the “chasm” between invention and product, also takes place. The spring term is an intensive experience and students should reserve sufficient time for the course activity. At the end of the spring term students will present their enterprise plan to a review panel of internal and external seasoned entrepreneurs and an audience of IP Fellows for feedback and discussion.

    Prerequisites

    ENGM 180; ENGM 187; ENGM 188

    Notes

    Students in the PhD Innovation Program normally take this course during the fourth year of their PhD program when their research is sufficiently advanced to have identified a new technology for possible commercialization. The course is open to any PhD student who has completed the prerequisite courses. Because of the reduced frequency of meeting, credit is given for only one course, one-half for the winter term and one-half for the spring term, but you only enroll in the course in the winter term. During one term of the same academic year that the students take ENGG 321, the students act as faculty assistants for ENGS 21 or ENGS 89/90 to gain experience in guiding and/or evaluating teams of students engaged in projects.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Eric R. Fossum


    Term: Winter 2024
    Time: Arrange
    Location: –
    Instructors:

    Eric R. Fossum


  • ENGS 324
    Microstrip Lines and Circuits

    Description

    Analysis of transmission structures and circuit elements at microwave frequencies. Microwave network representation. Characterization and sensitivities of transmission structure. Discontinuities. Two-dimensional planar components. Models for microwave semiconductor devices. Microwave networks.

    Prerequisites

    ENGS 61, ENGS 105, ENGS 120, and permission of instructor
  • ENGG 325
    Introduction to Surgical Innovation

    Description

    Analysis of transmission structures and circuit elements at microwave frequencies. Introduction to Surgical Innovation will engage students in an immersive experience, a cornerstone technique for innovative thinking and creative design. It comprises of three 10-week terms over one academic year (fall/general surgery, winter/surgical elective, and spring/surgical research). Student effort is approximately 20 hours per week (15 hours of activity and 5 hours to prepare assignments, read, think, and write). This unique course provides experiential learning on the life cycle of surgical devices, including: (1) defining a clinical need; (2) consideration of surgical risks and benefits from a patients point of view; (4) steps in the surgical procedure that could benefit from innovation to improve patient outcomes or make the procedure easier to perform; (5) managing surgical implants and instruments from a surgical scrub technologist’s point of view; (6) steps in surgical device procurement, processing, packaging, sterilization, and inventory management; (7) post-surgical patient care and device performance surveillance. The course begins in the fall term with a general surgery rotation. Engineering doctoral TSI (Training in Surgical Innovation) students work alongside 3rd year medical students and surgical residents. Each morning they attend the daily conference (e.g., indications, morbidity & mortality, journal club, tumor board, or grand rounds, 3-5h/wk). TSI students participate in the weekly medical student case discussion (2h) and also the weekly surgical resident simulation bioskills workshop (2h). Each student is assigned a surgeon proctor to help them navigate the clinical environment and understand context. Each week the student observes at least one outpatient clinic patient encounter (1-2h) and one surgical procedure (3-5h) with the proctor or another surgeon colleague arranged through the proctor. The outpatient clinic encounters focus on pre-operative patients to observe surgical consent discussions and post-operative patients to highlight surgical outcomes ascertainment and adverse event surveillance. On the day of surgery, the student arrives early to meet the surgical scrub technologist and help prepare for the surgery. The student then meets the patient preoperatively with the proctor and observes the surgical procedure from start to finish. The student follows the surgical scrub tech post-operatively to see instrument processing through central supply processing, sterilization and inventory management. Each week the student produces a 1-page write-up identifying opportunities for innovation to improve patient outcomes or easy of performance for the observed surgical procedure. The write-ups are evaluated and scored by Drs. Paulsen and Mirza. The winter term has a similar schedule with a different proctor (and set of surgeon colleagues) from a surgical subspecialty of the student’s choice, such as minimally invasive general surgery, oncologic surgery, otolaryngology, anesthesiology, neurosurgery or orthopedic surgery. The spring term is a research rotation in which students select a clinical mentor and an engineering mentor to guide development of a research proposal. The rotation focuses on medical research methods, including design of clinical trials, evaluation of benefits and harms, and standards for surgical materials/device performance and implant bioeffects. The rotation emphasizes clinical trial design and data analysis from a regulatory perspective. Activities include graduate courses engaging clinicians, engineers, other scientists, and the medical device industry to understand relevant FDA regulations and legislation, roles and responsibilities of federal advisory committees, types of applications (PMA/IDE/510k), review and consult processes, and role of device companies. Participants learn about the steps required to develop, protect, and finance an idea as a “laboratory” exercise and work to implement a specific idea (project), culminating in the development of a draft IP position and business plan. The focus of the training experience is on innovation and creation of new technology-driven start-up companies (not on business management). The final written assignment for the Surgical Innovation Course is a 6-page research proposal for development and validation of a novel surgical technology, similar in format to an NIH Small Business Innovation Research (SBIR) grant. The student also attends at least one hospital surgical implant purchasing committee meeting during the term and writes a one-page report on the device procurement decision-making process. Both the purchasing process write-up and research proposal are evaluated and scored by the student’s mentors and also by Drs. Paulsen and Mirza.

    Prerequisites

    Permission of Instructor Required

    Notes

    Three-term course. This course replaces ENGG 296.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Winter 2023
    Time: Arrange
    Location: –
    Instructors:

    Keith D. Paulsen


    Term: Spring 2023
    Time: Arrange
    Location: –
    Instructors:

    Keith D. Paulsen

    Thayer Faculty


    Term: Fall 2023
    Time: Arrange
    Location:

    TBD

    Instructors:

    Keith D. Paulsen

    Thayer Faculty


    Term: Winter 2024
    Time: Arrange
    Location: –
    Instructors:

    Keith D. Paulsen

    Thayer Faculty


    Term: Spring 2024
    Time: Arrange
    Location: –
    Instructors:

    Keith D. Paulsen

    Sohail K. Mirza


  • ENGG 332
    Topics in Plastic Flow and Fracture of Solids

    Description

    Advanced study may be pursued on topics related to the microscopic aspects of the plastic flow and fracture of solids. The topics extend those introduced in ENGS 130 and ENGS 132 by providing an in-depth examination of the methods of strengthening, brittle and ductile fracture, fatigue, creep, and superplasticity. The emphasis is on the mechanisms underlying the phenomena. Readings in the literature will be assigned, and the student will be required to prepare a detailed term paper.

    Prerequisites

    ENGS 130, ENGS 132, and permission of instructor

    Notes

    Cannot be used to satisfy any A.B. degree requirements
  • ENGG 339
    Advanced Electron Microscopy

    Description

    Image formation and contrast are discussed for the transmission electron microscope, using both kinematical and dynamical theory. Image simulation methods are outlined and the information from a variety of diffraction methods, such as CBED, are described. Various analytical techniques such as electron energy loss spectroscopy and x-ray fluorescence, including advanced techniques such as ALCHEMI, are covered. Emphasis is placed on the applications, resolution, and theoretical and practical limitations of each technique. There are several laboratory sessions, each requiring a report.

    Prerequisites

    ENGS 133 or permission of instructor

    Notes

    Cannot be used to satisfy any A.B. degree requirements
  • ENGG 365
    Advanced Biomaterials

    Description

    This course will focus on the interface between the host and implant with greater emphasis on the tissue reaction to metals, ceramics, polymers, bioceramics, and biopolymers than on the effect of the host environment on the materials. Ion release concerns, wear particle reactions, and the potential toxic properties of the salts of implant metals will be analyzed. The cells and cellular reactions available to the host will be evaluated in detail.

    Prerequisites

    ENGS 165 and permission of instructor.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: Arrange
    Location: –
    Instructors:

    Douglas W. Van Citters


  • ENGG 367
    Heat Transfer in Hyperthermia

    Description

    Review of coordinate systems, energy conservation equation, and temperature and heat-flux boundary conditions. Capillary blood perfusion as a distributed heat sink. Summary of distributed heat-flux sources associated with one or more of the following: internal and external radio-frequency, ultrasound, and microwave applicators. Surface cooling. Steady-state analytic and numerical solutions to practical problems in one and two dimensions. One or more of these advanced topics: transient responses, large blood vessels as discrete heat sinks, approximate solutions in three dimensions, lumped approximations to distributed systems.

    Prerequisites

    ENGS 23, ENGS 156, and permission of instructor
  • ENGM 387
    MEM Professional Skills

    Description

    This course develops professional skills required for professional success during and after the MEM program. Skills acquired provide a basis for success in pursuing, securing, and performing an internship and a post-graduation job. In a series of workshops conducted through the fall term, the course targets career self-assessment, ethics, interpersonal, and communication skills. Homework assignments provide practice and feedback for skills learned. ESL (English as a Second Language) support is offered as needed in the context of written and speaking activities of the course.

    Prerequisites

    No Prerequisite

    Notes

    Cannot be used to satisfy any AB, BE, MEng, MS, or PhD degree requirements

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Mon/Tues 3:30-5:20 PM, x-hour Mon 5:30-6:20 PM
    Location:

    MacLean B01

    Instructors:

    Jennifer St. Laurence


    Term: Fall 2024
    Time: G
    Location: –
    –

  • ENGG 390
    Master of Engineering Management Project

    Description

    An individual engineering project to be completed during any term of the final year of an MEM program. The project should define a practical need and propose a means to satisfy it, display an ability to conceive and evaluate solutions, describe appropriate analytical, experimental, and economic evaluations, and provide recommendations for further action. Projects will normally either have an industrial context or will be related to a specific design objective within a research program at Thayer School.

    Prerequisites

    ENGM 178 or permission of instructor

    Notes

    ENGM 178 or permission of instructor

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2023
    Time: –
    Location: –
    Instructors:

    Geoffrey G. Parker


    Term: Summer 2023
    Time: Arrange
    Location: –
    Instructors:

    Geoffrey G. Parker


    Term: Fall 2023
    Time: Arrange
    Location: –
    Instructors:

    Geoffrey G. Parker


    Term: Winter 2024
    Time: –
    Location: –
    Instructors:

    Geoffrey G. Parker


    Term: Spring 2024
    Time: –
    Location: –
    Instructors:

    Vikrant S. Vaze


    Term: Summer 2024
    Time: Arrange
    Location: –
    Instructors:

    Vikrant S. Vaze


  • ENGG 408
    Machine Learning

    Description

    Machine learning is a set of algorithms in the discipline of AI that enable various systems to learn and improve from data and experience without being explicitly given a set of rules or formulas. Machine learning can seem like magic sometimes, but a goal in this course is to learn that machine learning is not magic but, rather, is based on very rigorous mathematical and engineering principles with a vast number of applications. This course will start with requisite mathematical backgrounds (probability theory, statistics, some basic linear algebra, etc.). Then we will discuss unsupervised ML models, namely linear regression/classification models, neural network models, and kernel machine models. Finally, we will pivot to unsupervised learning and discuss unsupervised ML algorithms, such as graphical models, K-clustering algorithm, EM (Expectation Maximization) algorithm, autoencoders, PCA/ICA, etc. Programming using Python and ML software packages (PyTorch, Tensorflow, etc.) will be used to supplement your understanding of the mathematics and algorithms covered in this course and to develop large-scale applications of ML algorithms. The topics covered in this course are relevant for building, understanding, and analyzing a wide range of current state-of-the-art machine learning models and lay a strong theoretical foundation for understanding how the ideas of machine learning are used in fields such as economics, finance, policy-making, and healthcare, just to name a few.

    Notes

    This course is open only to students enrolled in the online MEng in Computer Engineering program.  This course cannot be used to satisfy any AB, BE, MEM, MS, PhD, or residential MEng degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: –
    Location:

    Online course

    Instructors:

    Peter Chin


  • ENGG 410
    Signal Processing

    Description

    Digital (or discrete-time) signal processing (DSP) is a part of a diverse array of systems and applications. The mathematical theories that underpin the discipline of signal processing are presented and used in applied settings, allowing you to analyze, optimize, and adjust a wide range of data and signals. You will learn topics such as sampling, signal filtering, noise reduction, the discrete Fourier transform (and fast Fourier transform), and spectrum analysis.

    Notes

    This course is open only to students enrolled in the online MEng in Computer Engineering program. This course cannot be used to satisfy any AB, BE, MEM, MS, PhD, or residential MEng degree requirements.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Spring 2024
    Time: –
    Location:

    Online course

    Instructors:

    Kelly C Seals


  • ENGG 462
    Embedded Systems

    Description

    This is a graduate-level course covering the different types of hardware platforms, software tools, and development techniques used in embedded systems. You will learn how to design, develop, prototype, test, and build microcontroller-based systems with an emphasis on sensing and processing for intelligent embedded systems.

    Notes

    This course is open only to students enrolled in the online MEng in Computer Engineering program. This course cannot be used to satisfy any AB, BE, MEM, MS, PhD, or residential MEng degree requirements.
  • ENGG 700
    Responsible & Ethical Conduct of Research

    Notes

    For new MS & PhD students only.

    Offered

    Term
    Time
    Location / Method
    Instructor(s)
    Term: Fall 2023
    Time: Tues 8:00-10:00 AM
    Location:

    ECSC 008

    Instructors:

    Molly Clark Carpenter