Electrical and Computer Engineering (E C E) 1

E C E 219 — ANALYTICAL METHODS FOR ELECTROMAGNETICS

ELECTRICAL ENGINEERING
2 credits.

AND COMPUTER Reviews basic calculations in electromagnetic engineering upon which

ENGINEERING (E C E)
all higher level concepts and physical model construction are based. It
emphasizes quantitative calculation mastery in three spatial dimensions.
Applies analysis tools from vector calculus to the calculation and
prediction of electrical system properties. Examples include calculating
E C E 1 — COOPERATIVE EDUCATION PROGRAM
electric and magnetic fields, electric potentials, total electric charge, and
1 credit.
electric flux from change or current sources.
Work experience which combines classroom theory with practical Requisites: MATH 234 or 376, or member of Engineering Guest Students
knowledge of operations to provide students with a background upon Repeatable for Credit: No
which to base a professional career. Last Taught: Fall 2023
Requisites: Sophomore standing or member of Engineering Guest
E C E 220 — ELECTRODYNAMICS I
Students
3 credits.
Course Designation: Workplace - Workplace Experience Course
Repeatable for Credit: Yes, unlimited number of completions Potential theory; static and dynamic electric and magnetic fields;
Last Taught: Spring 2024 macroscopic theory of dielectric and magnetic materials; Maxwell's
equations; boundary conditions; wave equation; introduction to
E C E 203 — SIGNALS, INFORMATION, AND COMPUTATION
transmission lines.
3 credits.
Requisites: (PHYSICS 202, 208, or 248) and E C E 219, or member of
Introduction to the signals, information, and computational techniques in Engineering Guest Students
electrical engineering. Repeatable for Credit: No
Requisites: (MATH 211, 217, 221, or 275) or member of Engineering Guest Last Taught: Spring 2024
Students
E C E 230 — CIRCUIT ANALYSIS
Repeatable for Credit: No
4 credits.
Last Taught: Spring 2024
Ohm's law, Kirchhoff's laws, resistive circuits, nodal and mesh analysis,
E C E 204 — DATA SCIENCE & ENGINEERING
superposition, equivalent circuits using Thevenin-Norton theories, op
3 credits.
amps and op amp circuits, first-order circuits, second-order circuits,
A hands-on introduction to Data Science using the Python programming sinusoidal steady state, phasors, RMS value, complex power, power factor,
language. Data-centric and computational thinking. Describe, analyze, and mutual inductance, linear and ideal transformers, ideal filters and transfer
make predictions using data from real-world phenomena. Programming functions.
in Python. Importing, manipulating, summarizing, and visualizing data of Requisites: (MATH 222 or 276) and (PHYSICS 202, 208, or 248), or
various types. Notions of bias, fairness, and ethics in data science. member of Engineering Guest Students
Requisites: MATH 112, 114, 171, or member of Engineering Guest Students Repeatable for Credit: No
Repeatable for Credit: No Last Taught: Spring 2024
Last Taught: Spring 2024
E C E/PHYSICS 235 — INTRODUCTION TO SOLID STATE
E C E 210 — INTRODUCTORY EXPERIENCE IN ELECTRICAL ELECTRONICS
ENGINEERING 3 credits.
2 credits.
An introduction to the physical principles underlying solid-state electronic
An introduction to electrical and electronic devices, circuits and systems and photonic devices, including elements of quantum mechanics, crystal
including software and hardware focusing on a real-world project. structure, semiconductor band theory, carrier statistics, and band
Requisites: None diagrams. Offers examples of modern semiconductor structures. Prior
Repeatable for Credit: No experience with MATLAB [such as E C E 203] is strongly encouraged but
Last Taught: Spring 2024 not required.
Requisites: (MATH 222 or 276) and (PHYSICS 202, 208, or 248), or
member of Engineering Guest Students
Course Designation: Level - Intermediate
L&S Credit - Counts as Liberal Arts and Science credit in L&S
Repeatable for Credit: No
Last Taught: Spring 2024
2 Electrical and Computer Engineering (E C E)

E C E/COMP SCI 252 — INTRODUCTION TO COMPUTER E C E 305 — SEMICONDUCTOR PROPERTIES LABORATORY

ENGINEERING 1 credit.
3 credits.
Introduction to some fundamental properties of semiconductor
Logic components built with transistors, rudimentary Boolean algebra, materials and devices through the use of characterization techniques
basic combinational logic design, basic synchronous sequential logic common in modern electronic industry. These concepts include: charge
design, basic computer organization and design, introductory machine- carriers; energy bands; space charge regions; carrier drift, diffusion and
and assembly-language programming. recombination; light emission; and lattice vibrations.
Requisites: None Requisites: E C E 271 and (E C E 335 or concurrent enrollment), or
Course Designation: Level - Elementary member of Engineering Guest Students
L&S Credit - Counts as Liberal Arts and Science credit in L&S Repeatable for Credit: No
Repeatable for Credit: No Last Taught: Spring 2020
Last Taught: Spring 2024
E C E 306 — LINEAR ACTIVE CIRCUITS LABORATORY
E C E 270 — CIRCUITS LABORATORY I 1 credit.
1 credit.
Direct coupled and operational amplifier characteristics; applications of
Experiments cover Kirchhoff's laws, inductors, basic operational amplifier feedback; practical aspects.
circuits, and frequency response. Requisites: E C E 271 and 340, or member of Engineering Guest
Requisites: E C E 210 and (E C E 230 or concurrent enrollment), or Students
member of Engineering Guest Students Repeatable for Credit: No
Repeatable for Credit: No Last Taught: Spring 2018
Last Taught: Spring 2024
E C E 308 — NONLINEAR ELECTRONIC CIRCUITS LABORATORY
E C E 271 — CIRCUITS LABORATORY II 1 credit.
1 credit.
An experimental study of selected nonlinear electronic circuits and devices
Experiments cover electronic device characteristics, limitations and using diodes, transistors, op-amps, timers, data converters, and logic
applications of operational amplifiers, and feedback circuits. components.
Requisites: E C E 270 and (E C E 340 or concurrent enrollment), or Requisites: E C E 271 and 340, or member of Engineering Guest
member of Engineering Guest Students Students
Repeatable for Credit: No Repeatable for Credit: No
Last Taught: Spring 2024 Last Taught: Fall 2017

E C E 303 — INTRODUCTION TO REAL-TIME DIGITAL SIGNAL E C E 313 — OPTOELECTRONICS LAB

PROCESSING 1 credit.
2 credits.
Light detection using photovoltaic and photoconductive detectors and
Emphasizes the implementation of DSP algorithms on a digital signal phototransistors. Light generation using light emitting diodes and laser
processor in "real-time." Many of the signal processing algorithms that diodes. Light transmission using optical fibers. Optoisolators and optical
were used in E C E 203 will be reviewed in MATLAB and then will be switches. Light emitting diode and liquid crystal displays.
implemented on a floating point signal processor in "real-time" using the Requisites: E C E 271 and 340, or member of Engineering Guest
C programming language. Explore many basic digital signal processing Students
processes in real-time. Gain the ability to create and develop your own Repeatable for Credit: No
Digital Signal Processing projects for a modern digital signal precessor Last Taught: Spring 2024
using an Integrated Development Environment. Lab hardware will be
provided. E C E 315 — INTRODUCTORY MICROPROCESSOR LABORATORY
Requisites: E C E 203 or member of Engineering Guest Students 1 credit.
Repeatable for Credit: No
Software and hardware experiments with a microcomputer system.
Last Taught: Spring 2024
Assembly language programming, simple input/output interfacing, and
E C E 304 — ELECTRIC MACHINES LABORATORY interrupt processing in microcomputer systems.
1 credit. Requisites: E C E 353 or concurrent enrollment, or member of
Engineering Guest Students
Terminal characteristics of electric machines, elements of speed control, Repeatable for Credit: No
voltage regulation, and applications in systems. Emphasis on the Last Taught: Spring 2024
experimental approach to the solution of complex physical problems.
Requisites: (E C E 355, 356, or concurrent enrollment) or member of
Engineering Guest Students
Repeatable for Credit: No
Last Taught: Spring 2024
 Electrical and Computer Engineering (E C E) 3

E C E 317 — SENSORS LABORATORY E C E 334 — STATE SPACE SYSTEMS ANALYSIS

1 credit. 3 credits.

A hands-on introduction to a variety of different sensor types. Labs Analysis of systems using matrix methods to write and solve state-variable
incorporate implementation concerns involving interference, isolation, differential equations. Additional topics include stability, controllability,
linearity, amplification, and grounding. observability, state feedback, observers, and dynamic output feedback.
Requisites: E C E 271 and (E C E 340 or concurrent enrollment), or Requisites: E C E 330, MATH 319, 320, 376, or member of Engineering
member of Engineering Guest Students Guest Students
Repeatable for Credit: No Repeatable for Credit: No
Last Taught: Spring 2024 Last Taught: Spring 2024

E C E 320 — ELECTRODYNAMICS II E C E 335 — MICROELECTRONIC DEVICES

3 credits. 3 credits.

Static and dynamic electromagnetic fields; forces and work in Characteristics of semiconductors; study of physical mechanisms and
electromechanical systems; magnetic circuits; plane wave propagation; circuit modeling of solid state electronic and photonic devices; principles
reflection of plane waves; generalized transmission line equations; of microelectronic processing and examples of integrated circuits.
current and voltage on transmission lines; impedance transformation and Requisites: (E C E 220, 230, and PHYSICS/E C E 235), or member of
matching; Smith charts. Engineering Guest Students
Requisites: E C E 220 or member of Engineering Guest Students Repeatable for Credit: No
Repeatable for Credit: No Last Taught: Spring 2024
Last Taught: Fall 2023
E C E 340 — ELECTRONIC CIRCUITS I
E C E 330 — SIGNALS AND SYSTEMS 3 credits.
3 credits.
A first course in modeling, characterization, and application of
Time-domain response and convolution; frequency-domain response semiconductor devices and integrated circuits. Development of
using Fourier series, Fourier transform, Laplace transform; discrete Fourier appropriate models for circuit-level behavior of diodes, bi-polar and field
series and transform; sampling; z-transform; relationships between effect transistors, and non-ideal op-amps. Application in analysis and
time and frequency descriptions of discrete and continuous signals and design of linear amplifiers. Frequency domain characterization of transistor
systems. circuits.
Requisites: E C E 203 or member of Engineering Guest Students Requisites: (E C E 203 and 230) or member of Engineering Guest
Repeatable for Credit: No Students
Last Taught: Spring 2024 Repeatable for Credit: No
Last Taught: Spring 2024
E C E 331 — INTRODUCTION TO RANDOM SIGNAL ANALYSIS AND
STATISTICS E C E 342 — ELECTRONIC CIRCUITS II
3 credits. 3 credits.

Introduction to probability, random variables, and random processes. A second course in modeling and application of semiconductor devices
Confidence intervals, introduction to experimental design and hypothesis and integrated circuits. Advanced transistor amplifier analysis, including
testing. Statistical averages, correlation, and spectral analysis for wide feedback effects. Design for power amplifiers, op-amps, analog filters,
sense stationary processes. Random signals and noise in linear systems. oscillators, A/D and D/A converters, and power converters. Introduction to
Requisites: (E C E 203 or 330) or member of Engineering Guest transistor level design of CMOS digital circuits.
Students Requisites: E C E 340 or member of Engineering Guest Students
Repeatable for Credit: No Repeatable for Credit: No
Last Taught: Fall 2023 Last Taught: Spring 2024

E C E 332 — FEEDBACK CONTROL SYSTEMS E C E/COMP SCI 352 — DIGITAL SYSTEM FUNDAMENTALS
3 credits. 3 credits.

Modeling of continuous systems; computer-aided solutions to systems Logic components, Boolean algebra, combinational logic analysis and
problems; feedback control systems; stability, frequency response and synthesis, synchronous and asynchronous sequential logic analysis and
transient response using root locus, frequency domain and state variable design, digital subsystems, computer organization and design.
methods. Requisites: Satisfied Quantitative Reasoning (QR) A requirement and
Requisites: E C E 330 or member of Engineering Guest Students E C E/COMP SCI 252
Repeatable for Credit: No Course Designation: Gen Ed - Quantitative Reasoning Part B
Last Taught: Fall 2023 Breadth - Physical Sci. Counts toward the Natural Sci req
Level - Intermediate
L&S Credit - Counts as Liberal Arts and Science credit in L&S
Repeatable for Credit: No
Last Taught: Spring 2024
4 Electrical and Computer Engineering (E C E)

E C E 353 — INTRODUCTION TO MICROPROCESSOR SYSTEMS E C E 370 — ADVANCED LABORATORY

3 credits. 2 credits.

Introduction to architecture, operation, and application of Experiments related to the required core material.
microprocessors; microprocessor programming; address decoding; system Requisites: E C E 271 and (E C E 340 or concurrent enrollment), or
timing; parallel, serial, and analog I/O; interrupts and direct memory member of Engineering Guest Students
access; interfacing to static and dynamic RAM; microcontrollers. Repeatable for Credit: No
Requisites: E C E/COMP SCI 252 and (COMP SCI 300 or 302 prior to Last Taught: Spring 2024
Fall 2018), or member of Engineering Guest Students
Repeatable for Credit: No E C E 376 — ELECTRICAL AND ELECTRONIC CIRCUITS
Last Taught: Spring 2024 3 credits.

E C E/COMP SCI 354 — MACHINE ORGANIZATION AND Ohm's law, Kirchhoff's laws, resistive circuits, nodal and mesh analysis,
PROGRAMMING superposition, equivalent circuits using Thevenin and Norton Theorems,
3 credits. op amps and op amp circuits, capacitors and inductors in first-order
circuits, sinusoidal steady state, phasors, RMS value, complex power,
An introduction to fundamental structures of computer systems and the power factor, mutual inductance, linear and ideal transformers.
C programming language with a focus on the low-level interrelationships Requisites: (MATH 222 or 276) and (PHYSICS 202, 208, or 248), or
and impacts on performance. Topics include the virtual address space and member of Engineering Guest Students. Not open to students with credit
virtual memory, the heap and dynamic memory management, the memory for E C E 230.
hierarchy and caching, assembly language and the stack, communication Repeatable for Credit: No
and interrupts/signals, compiling and assemblers/linkers. Last Taught: Spring 2024
Requisites: E C E/COMP SCI 252 and (COMP SCI 300 or 302) or
graduate/professional standing or declared in the Capstone Certificate in E C E 377 — FUNDAMENTALS OF ELECTRICAL AND ELECTRO-
Computer Sciences for Professionals MECHANICAL POWER CONVERSION
Course Designation: Gen Ed - Quantitative Reasoning Part B 3 credits.
Breadth - Natural Science
Fundamentals of electromagnetic induction and application to
Level - Intermediate
transformers and induction heating; Lorentz forces with a focus on the
L&S Credit - Counts as Liberal Arts and Science credit in L&S
operation and control of DC and AC motors and linear actuators; electrical
Repeatable for Credit: No
power conversion using power electronics for motor drives and direct
Last Taught: Spring 2024
power converters.
E C E 355 — ELECTROMECHANICAL ENERGY CONVERSION Requisites: (MATH 234 or 376), (PHYSICS 202, 208, or 248), and
3 credits. E C E 376, or member of Engineering Guest Students
Repeatable for Credit: No
Energy storage and conversion, force and emf production, coupled Last Taught: Spring 2024
circuit analysis of systems with both electrical and mechanical
inputs. Applications to electric motors and generators and other E C E 379 — SPECIAL TOPICS IN ELECTRICAL AND COMPUTER
electromechanical transducers. ENGINEERING
Requisites: E C E 230 or 376, graduate/professional standing, member of 1-4 credits.
Engineering Guest Students, or declared in Capstone Certificate in Power
Topics of special interest to undergrads in electrical and computer
Conversion and Control
engineering.
Repeatable for Credit: No
Requisites: Sophomore standing or member of Engineering Guest
Last Taught: Spring 2024
Students
E C E 356 — ELECTRIC POWER PROCESSING FOR ALTERNATIVE Repeatable for Credit: Yes, unlimited number of completions
ENERGY SYSTEMS Last Taught: Fall 2022
3 credits.
E C E 399 — INDEPENDENT STUDY
Introduction to electrical power processing technologies that are 1-3 credits.
necessary to convert energy from alternative sources into useful electrical
Directed study projects as arranged with instructor.
forms. Several specific alternative energy sources are examined, providing
Requisites: Consent of instructor
platforms for introducing basic concepts in power electronics, electric
Course Designation: Level - Advanced
machines, and adjustable-speed drives.
L&S Credit - Counts as Liberal Arts and Science credit in L&S
Requisites: (E C E 230 or 376) or member of Engineering Guest
Repeatable for Credit: Yes, unlimited number of completions
Students
Last Taught: Spring 2024
Repeatable for Credit: No
Last Taught: Fall 2021
 Electrical and Computer Engineering (E C E) 5

E C E 401 — ELECTRO-ACOUSTICAL ENGINEERING E C E 427 — ELECTRIC POWER SYSTEMS

3 credits. 3 credits.

Principles of plane and spherical sound waves; acoustical, mechanical, and The electric power industry, operation of power systems, load flow, fault
electrical analogies; electroacoustic transducer materials and techniques; calculations, economic dispatch, general technical problems of electric
specific types of transducers such as microphones and loudspeakers. power networks.
Requisites: E C E 203, graduate/professional standing, or member of Requisites: E C E 330, graduate/professional standing, or member of
Engineering Guest Students Engineering Guest Students
Repeatable for Credit: No Repeatable for Credit: No
Last Taught: Spring 2024 Last Taught: Fall 2023

E C E 411 — INTRODUCTION TO ELECTRIC DRIVE SYSTEMS E C E 431 — DIGITAL SIGNAL PROCESSING

3 credits. 3 credits.

Basic concepts of electric drive systems. Emphasis on system analysis Sampling continuous-time signals and reconstruction of continuous-time
and application. Topics include: dc machine control, variable frequency signals from samples; spectral analysis of signals using the discrete Fourier
operation of induction and synchronous machines, unbalanced operation, transform; the fast Fourier transform and fast convolution methods; z-
scaling laws, adjustable speed drives, adjustable torque drives, coupled transforms; finite and infinite impulse response filter design techniques;
circuit modeling of ac machines. signal flow graphs and introduction to filter implementation.
Requisites: (E C E 355, 356, or 377), graduate/professional standing, or Requisites: E C E 330, graduate/professional standing, or member of
member of Engineering Guest Students, or declared in Power Conversion Engineering Guest Students
and Control Capstone Certificate Repeatable for Credit: No
Course Designation: Grad 50% - Counts toward 50% graduate Last Taught: Spring 2024
coursework requirement
Repeatable for Credit: No E C E 432 — DIGITAL SIGNAL PROCESSING LABORATORY
Last Taught: Fall 2023 3 credits.

E C E 412 — POWER ELECTRONIC CIRCUITS Implementation of digital signal processing algorithms on special-purpose
3 credits. and general-purpose hardware. Use of assembly and high-level languages,
and simulator to develop and test IIR, FIR filters and the FFT for modern
Operating characteristics of power semiconductor devices such as Bipolar DSP chips. Scaling for fixed point arithmetic. Use of high level languages
Junction Transistors, IGBTs, MOSFETs and Thyristors. Fundamentals of to implement real time, object oriented component based DSP systems
power converter circuits including dc/dc converters, phase controlled in general purpose computers. DSP applications, including data and voice
ac/dc rectifiers and dc/ac inverters. Practical issues in the design and communication systems.
operation of converters. Requisites: E C E 330 and COMP SCI 300, graduate/professional
Requisites: E C E 342, graduate/professional standing, member of standing, or member of Engineering Guest Students
Engineering Guest Students, or declared in Capstone Certificate in Power Course Designation: Grad 50% - Counts toward 50% graduate
Conversion and Control coursework requirement
Course Designation: Grad 50% - Counts toward 50% graduate Repeatable for Credit: No
coursework requirement Last Taught: Spring 2023
Repeatable for Credit: No
Last Taught: Fall 2023 E C E 434 — PHOTONICS
3 credits.
E C E 420 — ELECTROMAGNETIC WAVE TRANSMISSION
3 credits. Introduction to ray optics, physical optics and interference, applications
of Fourier optics, absorption, dispersion, and polarization of light. Light
Transmission lines: frequency domain analysis of radio frequency sources, including lasers (gas, solid state, and semiconductor), modulation
and microwave transmission circuits including power relations and and detection of light.
graphical and computer methods. Electromagnetic waves: planar optical Requisites: PHYSICS/E C E 235 and (E C E 320, PHYSICS 322, or
components, pulse dispersion, phase front considerations for optical concurrent enrollment in either one), graduate/professional standing, or
components, conducting waveguides, dielectric waveguides. Radiation: member of Engineering Guest Students
retarded potentials, elemental dipoles, radiating antenna characterization, Course Designation: Grad 50% - Counts toward 50% graduate
receiving mode. coursework requirement
Requisites: E C E 320, graduate/professional standing, or member of Repeatable for Credit: No
Engineering Guest Students Last Taught: Spring 2024
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: No
Last Taught: Spring 2024
6 Electrical and Computer Engineering (E C E)

E C E/COMP SCI/MATH 435 — INTRODUCTION TO E C E 445 — SEMICONDUCTOR PHYSICS AND DEVICES

CRYPTOGRAPHY 3 credits.
3 credits.
Physics and properties of semiconductors, p-n junctions, metal-
Cryptography is the art and science of transmitting digital information in a semiconductor contacts, homojunction and heterojunction bipolar
secure manner. Provides an introduction to its technical aspects. transistor and physics, metal-oxide-semiconductor and heterostructure
Requisites: (MATH 320, 340, 341, or 375) or graduate/professional field-effect transistor and physics, thin-film resistors, memory devices,
standing or member of the Pre-Masters Mathematics (Visiting quantum devices.
International) Program Requisites: E C E 335, graduate/professional standing, or member of
Course Designation: Level - Advanced Engineering Guest Students
L&S Credit - Counts as Liberal Arts and Science credit in L&S Course Designation: Grad 50% - Counts toward 50% graduate
Repeatable for Credit: No coursework requirement
Last Taught: Spring 2024 Repeatable for Credit: No
Last Taught: Fall 2023
E C E 436 — COMMUNICATION SYSTEMS I
3 credits. E C E 447 — APPLIED COMMUNICATIONS SYSTEMS
3 credits.
Amplitude, frequency, pulse, and pulse-code modulation. Narrow-band
noise representation and signal-to-noise ratios for various modulation Analysis with design problems of electronic communications circuits.
schemes. Pulse shaping, timing recovery, carrier synchronization, and Emphasis on the nonlinear effects of large-signal operation of active
equalization. Sampling, quantization and coding. devices. Complete design of r.f. oscillator, amplifier, and mixer circuits.
Requisites: (E C E 203 or 330), graduate/professional standing, or Requisites: E C E 340 and 420, graduate/professional standing, or
member of Engineering Guest Students member of Engineering Guest Students
Repeatable for Credit: No Course Designation: Grad 50% - Counts toward 50% graduate
Last Taught: Fall 2023 coursework requirement
Repeatable for Credit: No
E C E 437 — COMMUNICATION SYSTEMS II Last Taught: Fall 2023
3 credits.
E C E 453 — EMBEDDED MICROPROCESSOR SYSTEM DESIGN
Statistical analysis of information transmission systems. Probability of 4 credits.
error, design of receivers for digital transmission through additive white
Gaussian noise channels and bandlimited channels. Spread spectrum Hardware and software design for modern microprocessor-based
communication systems. Channel capacity, source and error control embedded systems; study of the design process; emphasis on major team
coding. design project.
Requisites: (E C E 203 or 330), graduate/professional standing, or Requisites: E C E 315 and COMP SCI 300 (or COMP SCI 302 or 367
member of Engineering Guest Students prior to Fall 2018), or graduate/professional standing, not open to special
Repeatable for Credit: No students. Students with credit for E C E 454 or 554 may not enroll.
Last Taught: Spring 2024 Repeatable for Credit: No
Last Taught: Spring 2024
E C E/M E 439 — INTRODUCTION TO ROBOTICS
3 credits. E C E 454 — MOBILE COMPUTING LABORATORY
4 credits.
Hands-on introduction to key concepts and tools underpinning robotic
systems in use and development today. Intended to give students the End-to-end project management; teamwork; fundamentals of disciplined
tools to understand robotic systems, to explore robotics for their own development practices; introduction to mobile computing platforms and
purposes, and to pursue advanced study in the field. Students are systems; design, implementation, and deployment of mobile systems and
expected to have familiarity with a high level programming language such applications.
as Python (recommended), MATLAB, Java or Julia. Requisites: COMP SCI 400 (or COMP SCI 367 prior to Fall 2018), or
Requisites: Senior standing or member of Engineering Guest Students graduate/professional standing, not open to special students. Students
Repeatable for Credit: No with credit for E C E 453 or 554 may not enroll.
Last Taught: Fall 2023 Repeatable for Credit: No
Last Taught: Spring 2024
 Electrical and Computer Engineering (E C E) 7

E C E/B M E 462 — MEDICAL INSTRUMENTATION E C E 504 — ELECTRIC MACHINE & DRIVE SYSTEM LABORATORY
3 credits. 2-3 credits.

Design and application of electrodes, biopotential amplifiers, biosensors, Steady state and dynamic performance of electric machines in
therapeutic devices. Medical imaging. Electrical safety. Measurement of combination with power electronic converters. Parameter measurement,
ventilation, blood pressure and flow. performance evaluation, design of experimental procedures for problem
Requisites: E C E 340, graduate/professional standing, or member of solving, use of digital data acquisition systems and signal processing
Engineering Guest Students equipment in system evaluation.
Course Designation: Grad 50% - Counts toward 50% graduate Requisites: E C E 711 or concurrent enrollment
coursework requirement Course Designation: Grad 50% - Counts toward 50% graduate
Repeatable for Credit: No coursework requirement
Last Taught: Fall 2023 Repeatable for Credit: No
Last Taught: Summer 2023
E C E/B M E 463 — COMPUTERS IN MEDICINE
3 credits. E C E/COMP SCI 506 — SOFTWARE ENGINEERING
3 credits.
Study of microprocessor-based medical instrumentation. Emphasis
on real-time analysis of electrocardiograms. Labs and programming Ideas and techniques for designing, developing, and modifying large
project involve design of biomedical digital signal processing algorithms. software systems. Topics include software engineering processes;
Knowledge of computer programming language like C, C++ or Java, requirements and specifications; project team organization and
strongly encouraged. management; software architectures; design patterns; testing and
Requisites: E C E 330 and (COMP SCI 200, 220, 300, 301, or placement debugging; and cost and quality metrics and estimation. Students will work
into COMP SCI 300), graduate/professional standing, or member of in large teams on a substantial programming project.
Engineering Guest Students Requisites: (COMP SCI 367 or 400) and (COMP SCI 407, 536, 537, 545,
Course Designation: Grad 50% - Counts toward 50% graduate 559, 564, 570, 679 or E C E/COMP SCI 552) or graduate/professional
coursework requirement standing, or declared in the Capstone Certificate in Computer Sciences
Repeatable for Credit: No for Professionals
Last Taught: Spring 2024 Course Designation: Level - Advanced
L&S Credit - Counts as Liberal Arts and Science credit in L&S
E C E 466 — ELECTRONICS OF SOLIDS Repeatable for Credit: No
3 credits. Last Taught: Spring 2024

Electronic, optical and thermal properties of crystalline solids. Energy- E C E 511 — THEORY AND CONTROL OF SYNCHRONOUS
momentum dispersion of fundamental particles and excitations in MACHINES
solids leading to microscopic theories of conductivity, polarizability and 3 credits.
permeability. Influence of materials characteristics on the performance of
electronic and photonic devices. The idealized three phase synchronous machine time domain model
Requisites: (E C E 305 or 335), graduate/professional standing, or including saliency, time invariant form using Park's transformation, sudden
member of Engineering Guest Students short circuits and other transient conditions, reduced order models,
Repeatable for Credit: No excitation system and turbine/governor control, dynamics of multiple
Last Taught: Spring 2021 machine systems, transient stability and subsynchronous resonance.
Requisites: E C E 411 and 427, graduate/professional standing, or member
E C E 489 — HONORS IN RESEARCH of Engineering Guest Students
1-3 credits. Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Undergraduate honors research projects supervised by faculty members.
Repeatable for Credit: No
Requisites: Consent of instructor
Last Taught: Summer 2023
Course Designation: Honors - Honors Only Courses (H)
Repeatable for Credit: Yes, unlimited number of completions E C E 512 — POWER ELECTRONICS LABORATORY
Last Taught: Spring 2024 3 credits.

E C E 491 — SENIOR DESIGN PROJECT This laboratory introduces the student to measurement and simulation of
3 credits. important operating characteristics of power electronic circuits and power
semiconductor devices. Emphasis is on devices, circuits, gating methods
Engineering design projects supervised by faculty members.
and power quality.
Requisites: Consent of instructor
Requisites: E C E 412, graduate/professional standing, or member of
Repeatable for Credit: No
Engineering Guest Students
Last Taught: Spring 2023
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: No
Last Taught: Fall 2023
8 Electrical and Computer Engineering (E C E)

E C E/COMP SCI/I SY E 524 — INTRODUCTION TO OPTIMIZATION E C E/N E 528 — PLASMA PROCESSING AND TECHNOLOGY
3 credits. 3 credits.

Introduction to mathematical optimization from a modeling and solution Introduction to basic understanding and techniques. Plasma processing
perspective. Formulation of applications as discrete and continuous of materials for semiconductors, polymers, plasma spray coatings, ion
optimization problems and equilibrium models. Survey and appropriate implantation, etching, arcs, extractive metallurgy and welding. Plasma and
usage of basic algorithms, data and software tools, including modeling materials diagnostics.
languages and subroutine libraries. Requisites: PHYSICS 322 or E C E 320, graduate/professional standing,
Requisites: (COMP SCI 200, 220, 300, 301, 302, 310, or placement or member of Engineering Guest Students
into COMP SCI 300) and (MATH 320, 340, 341, or 375) or graduate/ Course Designation: Grad 50% - Counts toward 50% graduate
professional standing coursework requirement
Course Designation: Breadth - Natural Science Repeatable for Credit: No
Level - Intermediate Last Taught: Fall 2021
L&S Credit - Counts as Liberal Arts and Science credit in L&S
Repeatable for Credit: No E C E/COMP SCI/M E 532 — MATRIX METHODS IN MACHINE
Last Taught: Spring 2024 LEARNING
3 credits.
E C E/N E/PHYSICS 525 — INTRODUCTION TO PLASMAS
3 credits. Linear algebraic foundations of machine learning featuring real-world
applications of matrix methods from classification and clustering to
Basic description of plasmas: collective phenomena and sheaths, denoising and data analysis. Mathematical topics include: linear equations,
collisional processes, single particle motions, fluid models, equilibria, regression, regularization, the singular value decomposition, and iterative
waves, electromagnetic properties, instabilities, and introduction to kinetic algorithms. Machine learning topics include: the lasso, support vector
theory and nonlinear processes. Examples from fusion, astrophysical and machines, kernel methods, clustering, dictionary learning, neural networks,
materials processing processing plasmas. and deep learning. Previous exposure to numerical computing (e.g.
Requisites: (E C E 320 or PHYSICS 322), graduate/professional Matlab, Python, Julia, R) required.
standing, or member of Engineering Guest Students Requisites: (MATH 234, 320, 340, 341, or 375) and (E C E 203,
Course Designation: Breadth - Physical Sci. Counts toward the Natural COMP SCI 200, 220, 300, 301, 302, 310, 320, or placement into
Sci req COMP SCI 300), graduate/professional standing, or declared in Capstone
Level - Advanced Certificate in Computer Sciences for Professionals
L&S Credit - Counts as Liberal Arts and Science credit in L&S Course Designation: Breadth - Physical Sci. Counts toward the Natural
Grad 50% - Counts toward 50% graduate coursework requirement Sci req
Repeatable for Credit: No Level - Advanced
Last Taught: Spring 2024 L&S Credit - Counts as Liberal Arts and Science credit in L&S
Grad 50% - Counts toward 50% graduate coursework requirement
E C E/N E/PHYSICS 527 — PLASMA CONFINEMENT AND HEATING Repeatable for Credit: No
3 credits. Last Taught: Spring 2024

Principles of magnetic confinement and heating of plasmas for controlled E C E/COMP SCI 533 — IMAGE PROCESSING
thermonuclear fusion: magnetic field structures, single particle orbits, 3 credits.
equilibrium, stability, collisions, transport, heating, modeling and
diagnostics. Discussion of current leading confinement concepts: Mathematical representation of continuous and digital images; models of
tokamaks, tandem mirrors, stellarators, reversed field pinches, etc. image degradation; picture enhancement, restoration, segmentation, and
Requisites: E C E/N E/PHYSICS 525, graduate/professional standing, or coding; pattern recognition, tomography.
member of Engineering Guest Students Requisites: E C E 330 and (MATH 320 or 340), graduate/professional
Course Designation: Breadth - Physical Sci. Counts toward the Natural standing, or member of Engineering Guest Students
Sci req Course Designation: Breadth - Physical Sci. Counts toward the Natural
Level - Advanced Sci req
L&S Credit - Counts as Liberal Arts and Science credit in L&S Level - Advanced
Grad 50% - Counts toward 50% graduate coursework requirement L&S Credit - Counts as Liberal Arts and Science credit in L&S
Repeatable for Credit: No Grad 50% - Counts toward 50% graduate coursework requirement
Last Taught: Spring 2024 Repeatable for Credit: No
Last Taught: Fall 2023
 Electrical and Computer Engineering (E C E) 9

E C E 536 — INTEGRATED OPTICS AND OPTOELECTRONICS E C E 542 — INTRODUCTION TO MICROELECTROMECHANICAL

3 credits. SYSTEMS
3 credits.
Characteristics of semiconductors; study of physical mechanisms and
modeling of solid state electronic and photonic devices; principles of Introduction to MEMS technology, devices and systems. Fundamentals of
optoelectronic processing and examples of integrated optoelectronics. MEMS in fabrication, process integration, material mechanics of MEMS
Requisites: E C E 335 and (E C E 420 or 434), graduate/professional structures, sensors and actuators. Main topics in MEMS - microfluidics,
standing, or member of Engineering Guest Students optical MEMS, RF MEMS, BioMEMS, packaging, and CAD.
Course Designation: Grad 50% - Counts toward 50% graduate Requisites: (E C E 335 or 340), graduate/professional standing, or
coursework requirement member of Engineering Guest Students
Repeatable for Credit: No Course Designation: Grad 50% - Counts toward 50% graduate
Last Taught: Fall 2023 coursework requirement
Repeatable for Credit: No
E C E 537 — COMMUNICATION NETWORKS Last Taught: Fall 2023
3 credits.
E C E 545 — ADVANCED MICROWAVE MEASUREMENTS FOR
Study of communication networks with focus on performance analysis. COMMUNICATIONS
Layered network structure. Basic protocol functions such as addressing, 3 credits.
multiplexing, routing, forwarding, flow control, error control, and
congestion response. Overview of transport, network, and link layer Measurements at VHF and microwave frequencies; characteristics of
protocol standards. Introduction to wireless and mobile networks. microwave generators, amplifiers, passive devices and detection systems;
Requisites: E C E 203 and (COMP SCI 400 or 367 prior to Fall 2018), measurement of frequency, noise and simple antenna patterns; time
graduate/professional standing, or member of Engineering Guest domain reflectometry, swept frequency network and spectrum analyzer
Students techniques; lecture and lab.
Repeatable for Credit: No Requisites: (E C E 440 or 447), graduate/professional standing, or
Last Taught: Fall 2022 member of Engineering Guest Students
Course Designation: Grad 50% - Counts toward 50% graduate
E C E/COMP SCI/M E 539 — INTRODUCTION TO ARTIFICIAL coursework requirement
NEURAL NETWORKS Repeatable for Credit: No
3 credits. Last Taught: Spring 2021

Theory and applications of artificial neural networks: multi-layer E C E/PHYSICS 546 — LASERS
perceptron, self-organization mapdeep neural network convolutional 2-3 credits.
neural network, recurrent network, support vector machines genetic
algorithm, and evolution computing. Applications to control, pattern General principles of laser operation; laser oscillation conditions; optical
recognition, prediction, and object detection and tracking. resonators; methods of pumping lasers, gas discharge lasers, e-beam
Requisites: COMP SCI 200, 220, 300, 301, 302, 310, placement into pumped lasers, solid state lasers, chemical lasers, and dye lasers; gain
COMP SCI 300, or graduate/professional standing measurements with lasers; applications of lasers.
Course Designation: Level - Advanced Requisites: (PHYSICS 322 or E C E 420) and (PHYSICS 449, 531, or
L&S Credit - Counts as Liberal Arts and Science credit in L&S 545), graduate/professional standing, or member of Engineering Guest
Repeatable for Credit: No Students
Last Taught: Spring 2024 Course Designation: Breadth - Physical Sci. Counts toward the Natural
Sci req
E C E 541 — ANALOG MOS INTEGRATED CIRCUIT DESIGN Level - Advanced
3 credits. L&S Credit - Counts as Liberal Arts and Science credit in L&S
Repeatable for Credit: No
Analysis, design and applications of modern analog circuits using
Last Taught: Fall 2015
integrated bipolar and field-effect transistor technologies. Provides the
student with a working knowledge of the basic circuits used in modern E C E 547 — ADVANCED COMMUNICATIONS CIRCUIT DESIGN
analog integrated circuits and techniques for analysis and design. 3 credits.
Requisites: E C E 340, graduate/professional standing, or member of
Engineering Guest Students Principles underlying the design of r.f. and microwave communications
Course Designation: Grad 50% - Counts toward 50% graduate circuits. Analysis and design of wideband nonlinear power amplifiers, S-
coursework requirement parameter techniques for r.f. active circuit design, computer aided design
Repeatable for Credit: No techniques, r.f. integrated circuits, fundamentals of low noise r.f. design.
Last Taught: Fall 2017 Requisites: (E C E 420 or 447), graduate/professional standing, or
member of Engineering Guest Students
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: No
Last Taught: Spring 2024
10 Electrical and Computer Engineering (E C E)

E C E 548 — INTEGRATED CIRCUIT DESIGN E C E 553 — TESTING AND TESTABLE DESIGN OF DIGITAL
3 credits. SYSTEMS
3 credits.
Bipolar and MOS devices in monolithic circuits. Device physics, fabrication
technology. IC-design for linear and nonlinear circuitry. Faults and fault modeling, test equipment, test generation for
Requisites: E C E 335, graduate/professional standing, or member of combinational and sequential circuits, fault simulation, memory and
Engineering Guest Students microprocessor testing, design for testability, built-in self-test techniques,
Repeatable for Credit: No and fault location.
Last Taught: Fall 2023 Requisites: E C E/COMP SCI 352, E C E 353, and (COMP SCI 400 or
367 prior to Fall 2018), graduate/professional standing, or member of
E C E 549 — INTEGRATED CIRCUIT FABRICATION LABORATORY Engineering Guest Students
4 credits. Repeatable for Credit: No
Last Taught: Spring 2024
Monolithic integrated circuit fabrication; mask making, photolithography,
oxidation, diffusion, junction evaluation, metallization, packaging, and E C E 554 — DIGITAL ENGINEERING LABORATORY
testing. 4 credits.
Requisites: (E C E 335 or 548), graduate/professional standing, or
member of Engineering Guest Students Practical aspects of computer system design. Design, construction,
Repeatable for Credit: No and testing of significant digital subsystems. Design, construction, and
Last Taught: Spring 2024 programming of pipelined digital computers.
Requisites: E C E 551 and E C E/COMP SCI 552, not open to special
E C E 551 — DIGITAL SYSTEM DESIGN AND SYNTHESIS students. Students with credit for E C E 453 or 454 may not enroll.
3 credits. Repeatable for Credit: No
Last Taught: Spring 2024
Introduction to the use of hardware description languages and automated
synthesis in design. Advanced design principles. Verilog and VHDL E C E 555 — DIGITAL CIRCUITS AND COMPONENTS
description languages. Synthesis from hardware description languages. 3 credits.
Timing-oriented synthesis. Relation of integrated circuit layout to timing-
oriented design. Design for reuse. Principles and characterization of logic circuits. Design and analysis
Requisites: E C E/COMP SCI 352, graduate/professional standing, or techniques for applied logic circuits. Transmission lines in digital
member of Engineering Guest Students applications. Families of circuit logic currently in use and their
Repeatable for Credit: No characteristics.
Last Taught: Spring 2024 Requisites: (E C E/COMP SCI 352 and E C E 340), graduate/
professional standing, or member of Engineering Guest Students
E C E/COMP SCI 552 — INTRODUCTION TO COMPUTER Repeatable for Credit: No
ARCHITECTURE Last Taught: Fall 2023
3 credits.
E C E 556 — DESIGN AUTOMATION OF DIGITAL SYSTEMS
The design of computer systems and components. Processor 3 credits.
design, instruction set design, and addressing; control structures
and microprogramming; memory management, caches, and memory Use of digital computers to simulate, partition, place and interconnect
hierarchies; and interrupts and I/O structures. E C E 551 or knowledge of digital electronic systems.
Verilog is recommended. Requisites: E C E/COMP SCI 352 and (COMP SCI 300 or 367 prior to
Requisites: (E C E/COMP SCI 352 and E C E/COMP SCI 354) or Fall 2018), graduate/professional standing, or member of Engineering
graduate/professional standing Guest Students
Course Designation: Breadth - Physical Sci. Counts toward the Natural Repeatable for Credit: No
Sci req Last Taught: Spring 2024
Level - Advanced
L&S Credit - Counts as Liberal Arts and Science credit in L&S
Repeatable for Credit: No
Last Taught: Spring 2024
 Electrical and Computer Engineering (E C E) 11

E C E/COMP SCI 561 — PROBABILITY AND INFORMATION THEORY E C E 601 — SPECIAL TOPICS IN ELECTRICAL AND COMPUTER
IN MACHINE LEARNING ENGINEERING
3 credits. 1-4 credits.

Probabilistic tools for machine learning and analysis of real-world datasets. Advanced topics of special interest to students in various areas of
Introductory topics include classification, regression, probability theory, Electrical and Computer Engineering.
decision theory and quantifying information with entropy, relative entropy Requisites: Junior standing or member of Engineering Guest Students
and mutual information. Additional topics include naive Bayes, probabilistic Repeatable for Credit: Yes, unlimited number of completions
graphical models, discriminant analysis, logistic regression, expectation Last Taught: Fall 2023
maximization, source coding and variational inference.
Requisites: (MATH 320, 340, 341, 375, or M E/COMP SCI/E C E 532 or E C E 610 — SEMINAR IN ELECTRICAL AND COMPUTER
concurrent enrollment) and (E C E 331, STAT/MATH 309, 431, STAT 311, ENGINEERING
324, M E/STAT 424 or MATH 531) or grad/profsnl standing or declared in 1 credit.
Capstone Certificate in Computer Sciences for Professionals
Survey of topics within the department of electrical and computer
Course Designation: Level - Advanced
engineering that introduce students to the materials/techniques to assist
L&S Credit - Counts as Liberal Arts and Science credit in L&S
them in being successful graduate students. Faculty seminars spanning
Grad 50% - Counts toward 50% graduate coursework requirement
energy and power systems, applied physics, electromagnetic fields,
Repeatable for Credit: No
plasmas, communications and signal processing, controls, photonics, solid
Last Taught: Fall 2023
state, and computers will be given. Additionally, students will participate
E C E/I SY E 570 — ETHICS OF DATA FOR ENGINEERS in weekly group exercises to enhance their skills in engineering/technical
3 credits. communications, writing, ethics, and project management.
Requisites: Graduate/professional standing
Introduction to ethical issues in data engineering and principled solutions. Course Designation: Grad 50% - Counts toward 50% graduate
Algorithmic fairness (individual fairness, group fairness, counterfactual coursework requirement
fairness), differential privacy and its applications, and robustness. Repeatable for Credit: No
Requisites: I SY E 521, 562, M E/COMP SCI/E C E 532, 539, or graduate/ Last Taught: Fall 2023
professional standing
Repeatable for Credit: No E C E 611 — INTRODUCTION TO DOCTORAL RESEARCH IN
Last Taught: Spring 2024 ELECTRICAL & COMPUTER ENGINEERING
2 credits.
E C E/M E 577 — AUTOMATIC CONTROLS LABORATORY
4 credits. A focus on topics within the department of electrical and computer
engineering that introduce students to the materials/techniques that
Control theory is reduced to engineering practice through the analysis and will assist them in being successful graduate students. Faculty seminars
design of actual systems in the laboratory. Experiments are conducted spanning energy and power systems, applied physics, electromagnetic
with modern servo systems using both analog and digital control. Systems fields, plasmas, communications and signal processing, controls,
identification and modern controls design are applied to motion and photonics, solid state, and computers will be given. Additionally, students
torque control. will participate in weekly group exercises to enhance their skills in
Requisites: M E 346 or E C E 332, or graduate/professional standing or engineering/technical communications, writing, ethics, and project
member of Engineering Guest Students management. Graded homework and a final project are assigned.
Course Designation: Grad 50% - Counts toward 50% graduate Requisites: Graduate/professional standing
coursework requirement Course Designation: Grad 50% - Counts toward 50% graduate
Repeatable for Credit: No coursework requirement
Last Taught: Spring 2024 Repeatable for Credit: No
Last Taught: Spring 2024
E C E 600 — SEMINAR IN ELECTRICAL AND COMPUTER
ENGINEERING
0 credits.

Weekly or bi-weekly seminars on topics in electrical and computer

engineering including automatic control, biomedical engineering,
communications and signal processing, computer engineering,
electromagnetic fields, energy and power systems, photonics, plasma, and
solid state. Seminar on a particular topic may include lectures given by
faculty, invited speakers, as well as group discussion.
Requisites: None
Repeatable for Credit: Yes, unlimited number of completions
Last Taught: Spring 2016
12 Electrical and Computer Engineering (E C E)

E C E/MATH 641 — INTRODUCTION TO ERROR-CORRECTING E C E/COMP SCI 707 — MOBILE AND WIRELESS NETWORKING
CODES 3 credits.
3 credits.
Design and implementation of protocols, systems, and applications for
Coding theory. Codes (linear, Hamming, Golay, dual); decoding-encoding; mobile and wireless networking, particularly at the media access control,
Shannon's theorem; sphere-packing; singleton and Gilbert-Varshamov network, transport, and application layers. Focus is on the unique problems
bounds; weight enumerators; MacWilliams identities; finite fields; other and challenges presented by the properties of wireless transmission,
codes (Reed-Muller, cyclic, BCH, Reed-Solomon) and error-correction various device constraints such as limited battery power, and node
algorithms. mobility. Knower of computer networking is strongly encouraged, such as
Requisites: MATH 541 or graduate/professional standing or member of from COMP SCI 640 or E C E 537.
the Pre-Masters Mathematics (Visiting International) Program Requisites: Graduate/professional standing
Course Designation: Breadth - Natural Science Course Designation: Grad 50% - Counts toward 50% graduate
Level - Advanced coursework requirement
L&S Credit - Counts as Liberal Arts and Science credit in L&S Repeatable for Credit: No
Grad 50% - Counts toward 50% graduate coursework requirement Last Taught: Spring 2024
Repeatable for Credit: No
Last Taught: Fall 2017 E C E 711 — DYNAMICS AND CONTROL OF AC DRIVES
3 credits.
E C E 697 — CAPSTONE PROJECT IN MACHINE LEARNING AND
SIGNAL PROCESSING Principles of power converters, two axis models of AC machines and AC
5 credits. drives, simulation of drive systems, analytical modeling of drives, dynamic
behavior of induction and synchronous motors and drive systems.
Individual or team project to gain hands-on-experience applying machine Requisites: E C E 411 and graduate/professional standing
learning and signal processing concepts. Course Designation: Grad 50% - Counts toward 50% graduate
Requisites: Graduate/professional standing coursework requirement
Course Designation: Grad 50% - Counts toward 50% graduate Repeatable for Credit: No
coursework requirement Last Taught: Spring 2024
Repeatable for Credit: No
Last Taught: Summer 2023 E C E 712 — SOLID STATE POWER CONVERSION
3 credits.
E C E 699 — ADVANCED INDEPENDENT STUDY
1-6 credits. Advanced course in power electronics which provides an understanding
of switching power converters. Included are DC-to-DC, AC-to-DC, DC-
Directed study projects as arranged with instructor. to-AC, and AC-to-AC converters, commutation techniques, converter
Requisites: Consent of instructor control, interfacing converters with real sources and loads.
Course Designation: Level - Advanced Requisites: E C E 412 and graduate/professional standing
L&S Credit - Counts as Liberal Arts and Science credit in L&S Course Designation: Grad 50% - Counts toward 50% graduate
Grad 50% - Counts toward 50% graduate coursework requirement coursework requirement
Repeatable for Credit: Yes, unlimited number of completions Repeatable for Credit: No
Last Taught: Spring 2024 Last Taught: Spring 2024

E C E 702 — GRADUATE COOPERATIVE EDUCATION PROGRAM E C E 713 — ELECTROMAGNETIC DESIGN OF AC MACHINES

1-2 credits. 3 credits.

Work experience that combines classroom theory with practical knowledge Electromagnetic design concepts and application to AC machines,
of operations to provide students with a background on which to develop magnetic circuit concepts, calculation of equivalent circuit parameters of
and enhance a professional career. The work experience is tailored for MS induction, synchronous and permanent magnet machines from geometric
students from within the U.S. as well as eligible international students. data, copper and iron loss calculations, theory and application of finite
Requisites: Graduate/professional standing elements to electromagnetic devices.
Course Designation: Grad 50% - Counts toward 50% graduate Requisites: (E C E 411 or 511) and graduate/professional standing
coursework requirement Course Designation: Grad 50% - Counts toward 50% graduate
Repeatable for Credit: Yes, unlimited number of completions coursework requirement
Last Taught: Spring 2024 Repeatable for Credit: No
Last Taught: Spring 2023
 Electrical and Computer Engineering (E C E) 13

E C E 714 — UTILITY APPLICATION OF POWER ELECTRONICS E C E/B M I/COMP SCI/MED PHYS 722 — COMPUTATIONAL
3 credits. OPTICS AND IMAGING
3 credits.
Power electronic application to utility systems is a rapidly growing field
with major impact on the industry. Covers material on HVDC transmission, Computational imaging includes all imaging methods that produce
energy storage systems, renewable sources, static compensators, and images as a result of computation on collected signals. Learn the tools
flexible ac transmission systems. to design new computational imaging methods to solve specific imaging
Requisites: E C E 412, 427, and graduate/professional standing problems. Provides an understanding of the physics of light propagation
Course Designation: Grad 50% - Counts toward 50% graduate and measurement, and the computational tools to model it, including wave
coursework requirement propagation, ray tracing, the radon transform, and linear algebra using
Repeatable for Credit: No matrix and integral operators and the computational tools to reconstruct
Last Taught: Spring 2022 an image, including linear inverse problems, neural networks, convex
optimization, and filtered back-projection. Covers a variety of example
E C E 717 — LINEAR SYSTEMS computational imaging techniques and their applications including
3 credits. coded apertures, structured illumination, digital holography, computed
tomography, imaging through scattering media, compressed sensing, and
Equilibrium points and linearization; natural and forced response of state
non-line-of-sight imaging.
equations; system equivalence and Jordan form; Lyapunov, asymptotic,
Requisites: Graduate/professional standing
and BIBO stability; controllability and duality; control-theoretic concepts
Course Designation: Grad 50% - Counts toward 50% graduate
such as pole-placement, stabilization, observers, dynamic compensation,
coursework requirement
and the separation principle. Knowledge of linear algebra [such as
Repeatable for Credit: No
MATH 340] required.
Requisites: Graduate/professional standing E C E 723 — ON-LINE CONTROL OF POWER SYSTEMS
Course Designation: Grad 50% - Counts toward 50% graduate 3 credits.
coursework requirement
Repeatable for Credit: No State estimation based on line-flow measurements. Detection and
Last Taught: Fall 2023 correction of incorrect on-line measurements. Reduction techniques.
Network security evaluation. On-line contingency studies and contingency
E C E 719 — OPTIMAL SYSTEMS remedial action. Calculation of penalty factors and optimal power dispatch
3 credits. strategies. On-line stability determination. Parallel processors for on-line
studies. Knowledge of basic probability analysis [such as E C E 331, STAT/
Optimality considerations in the study of dynamical systems; applications
MATH 431, or STAT 311] strongly encouraged.
to electrical systems gain selection, tuning, conditions for optimality,
Requisites: Graduate/professional standing
feedback and instability, iterative methods, filtering, prediction,
Course Designation: Grad 50% - Counts toward 50% graduate
smoothing, dynamic programming controller synthesis, stability and
coursework requirement
robustness criteria. Knowledge of State Space System Analysis [such as
Repeatable for Credit: No
E C E 334] strongly encouraged.
Last Taught: Spring 2024
Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate E C E/N E/PHYSICS 724 — WAVES AND INSTABILITIES IN
coursework requirement PLASMAS
Repeatable for Credit: No 3 credits.
Last Taught: Spring 2018
Waves in a cold plasma, wave-plasma interactions, waves in a hot plasma,
Landau damping, cyclotron damping, magneto-hydrodynamic equilibria
and instabilities, microinstabilities, introduction to nonlinear processes,
and experimental applications. Basic knowledge of plasmas [such as
PHYSICS/E C E/N E 525] and advanced electromagnetics [such as
PHYSICS 721 or E C E 740] strongly encouraged.
Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: No
Last Taught: Fall 2023
14 Electrical and Computer Engineering (E C E)

E C E/N E/PHYSICS 725 — PLASMA KINETIC THEORY AND E C E 731 — ADVANCED POWER SYSTEM ANALYSIS
RADIATION PROCESSES 3 credits.
3 credits.
Electrical transients due to faults and switching. Effect on power
Coulomb Collisions, Boltzmann equation, Fokker-Planck methods, system design and operation. Traveling waves and surge protection.
dynamical friction, neoclassical diffusion, collision operators radiation Computerized analysis of power transients.
processes and experimental applications. Basic knowledge of plasmas Requisites: E C E 427 and graduate/professional standing
[such as PHYSICS/E C E/N E 525] and advanced electromagnetics [such Course Designation: Grad 50% - Counts toward 50% graduate
as PHYSICS 721 or E C E 740] strongly encouraged. coursework requirement
Requisites: Graduate/professional standing Repeatable for Credit: No
Course Designation: Grad 50% - Counts toward 50% graduate Last Taught: Fall 2021
coursework requirement
Repeatable for Credit: No E C E 734 — VLSI ARRAY STRUCTURES FOR DIGITAL SIGNAL
Last Taught: Spring 2024 PROCESSING
3 credits.
E C E/N E/PHYSICS 726 — PLASMA MAGNETOHYDRODYNAMICS
3 credits. An overview of the architectures and design methodologies of VLSI
array processors for digital signal processing. Emphasis is placed on the
MHD equations and validity in hot plasmas; magnetic structure and techniques of mapping algorithms onto array structures for real time signal
magnetic flux coordinates; equilibrium in various configurations; stability processing. Knowledge of digital signal processing [such as E C E 431]
formulation, energy principle, classification of instabilities; ideal and and computer architecture [such as E C E/COMP SCI 552] strongly
resistive instability in various configurations, evolution of nonlinear encouraged.
tearing modes; force-free equilibria, helicity, MHD dynamo; experimental Requisites: Graduate/professional standing
applications. Basic knowledge of plasmas [such as PHYSICS/E C E/ Course Designation: Grad 50% - Counts toward 50% graduate
N E 525] and advanced electromagnetics [such as PHYSICS 721 or coursework requirement
E C E 740] strongly encouraged. Repeatable for Credit: No
Requisites: Graduate/professional standing Last Taught: Spring 2022
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement E C E 735 — SIGNAL SYNTHESIS AND RECOVERY TECHNIQUES
Repeatable for Credit: No 3 credits.
Last Taught: Spring 2023
Signals and their representation. Signal synthesis subject to constraints
E C E 729 — INFORMATION THEORY on peak voltage, energy, duration-bandwidth product. The theory of
3 credits. alternating projections onto convex sets and applications to inverse
problems in signal processing: signal recovery using incomplete data,
Definition of measures of information and their properties, capacity of image recovery in tomography using limited views, phase retrieval in
discrete and continuous channels with noise, source and channel coding optical astronomy.
theorems, fundamentals of channel coding, noiseless source coding, and Requisites: Graduate/professional standing
source coding with a fidelity criterion. Knowledge of basic probability Course Designation: Grad 50% - Counts toward 50% graduate
analysis [such as E C E 331, STAT/MATH 431, or STAT 311] required. coursework requirement
Requisites: Graduate/professional standing Repeatable for Credit: No
Course Designation: Grad 50% - Counts toward 50% graduate Last Taught: Spring 2020
coursework requirement
Repeatable for Credit: No E C E 736 — WIRELESS COMMUNICATIONS
Last Taught: Spring 2022 3 credits.

E C E 730 — PROBABILITY AND RANDOM PROCESSES Theory, design and analysis of mobile wireless communication systems
3 credits. from a signal processing perspective. Emphasis on code-division
multiple-access (CDMA) systems employing direct-sequence spread-
Review of basic probability. Advanced probability concepts. Random spectrum (DS-SS) signaling. Topics include characterization of mobile
vectors; linear filtering of random processes; stationarity; power spectral wireless channels, demodulation of DS-SS signals, diversity techniques,
densities; estimation; convergence; Markov chains; Poisson process; interference suppression methods, and low-complexity adaptive receivers.
Wiener process. Knowledge of basic probability analysis [such as E C E 331, Knowledge of probability [such as E C E 730] and digital communication
STAT/MATH 431, or STAT 311] strongly encouraged. [such as E C E 437] strongly encouraged.
Requisites: Graduate/professional standing Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement coursework requirement
Repeatable for Credit: No Repeatable for Credit: No
Last Taught: Fall 2023 Last Taught: Spring 2023
 Electrical and Computer Engineering (E C E) 15

E C E 738 — ADVANCED DIGITAL IMAGE PROCESSING E C E 742 — COMPUTATIONAL METHODS IN ELECTROMAGNETICS

3 credits. 3 credits.

Deterministic and stochastic spatio-temporal image models, transform Computational techniques for solving differential and integral equations
domain processing, Markov random fields and anisotropic diffusion; MAP that govern static, frequency-domain, and time-domain electromagnetic
parameter estimation, ill-posed inverse problems, robust statistics and field phenomena. Applications of the finite-difference time-domain
non-linear digital filtering in image processing. Applications to image method, finite-element method, and method of moments to practical
restoration, motion estimation, (video) image compression (MPEG, electromagnetics engineering problems. Knowledge of high-level
JPEG) and tomography. Knowledge of image processing [such as E C E/ programming language like MATLAB strongly encouraged. Knowledge of
COMP SCI 533] strongly encouraged. electromagnetics [such as E C E 320] strongly encouraged.
Requisites: Graduate/professional standing Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement coursework requirement
Repeatable for Credit: No Repeatable for Credit: No
Last Taught: Spring 2023 Last Taught: Spring 2024

E C E/M E 739 — KINEMATICS, DYNAMICS, AND CONTROL OF E C E 743 — HIGH-POWER DIODE LASERS AND AMPLIFIERS
ROBOTIC MANIPULATORS 3 credits.
3 credits.
Single-mode diode lasers and amplifiers and their applications; an
Robotics analysis and design, focusing on the analytical fundamentals in-depth treatment of the four basic types of high-power coherent
specific to robotic manipulators. Serial chain robotic manipulator forward diodes: phase-locked arrays, master-oscillator power amplifiers, unstable
and inverse kinematics, differential kinematics, dynamics, motion planning, resonators, and external-cavity-controlled resonators. Knowledge of
and controls. Knowledge of linear algebra [such as MATH 320], high- electromagnetics [such as E C E 320] and solid-state electronics [such as
level computational programming language such as MATLAB, and system E C E 335] strongly encouraged.
dynamics [such as M E 340] strongly encouraged. Requisites: Graduate/professional standing
Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate
Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement
coursework requirement Repeatable for Credit: No
Repeatable for Credit: No Last Taught: Spring 2020
Last Taught: Spring 2023
E C E 744 — THEORY OF MICROWAVE CIRCUITS AND DEVICES
E C E 740 — ELECTROMAGNETIC THEORY 3 credits.
3 credits.
Scattering matrices; symmetrical junctions; impedance and ABCD
Time harmonic fields and waves in linear media with applications to matrices; equivalent circuits. Wave propagation in periodic structures
radiation, guiding and scattering; wave and surface impedance and and anisotropic media; Floquet's theorem; Brillouin diagrams; Hartree
admittance concepts; duality, uniqueness, image theory, equivalence harmonics; tensor permeability, conductivity, and permittivity; coupled
principle, induction and compensation theorems, reciprocity, Green's wave equations; normal modes; applications in ferrite devices. Knowledge
functions, wave functions, potential and transform theory. Knowledge of of advanced engineering electromagnetics [such as E C E 740] strongly
electromagnetics [such as E C E 420] strongly encouraged. encouraged.
Requisites: Graduate/professional standing Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement coursework requirement
Repeatable for Credit: No Repeatable for Credit: No
Last Taught: Fall 2023 Last Taught: Spring 2022

E C E 741 — SEMICONDUCTOR DIODE LASERS AND OTHER E C E 745 — SOLID STATE ELECTRONICS
OPTOELECTRONIC DEVICES 3 credits.
3 credits.
Physical principles underlying the action of semiconductor devices,
An overview of modern photonic technology and an introduction to chemical bonding and energy band structure, Boltzmann transport
key parameters and concepts; the basic mechanisms determining the theory, optical and high frequency effects, diffusion and drift, interfaces,
relationship between optical gain and current density, and quantum- properties of elemental and compound semiconductors.
well laser structures; physics of high-power phase-locked laser arrays Requisites: Graduate/professional standing
or other optoelectronics devices. Knowledge of electromagnetics [such Course Designation: Grad 50% - Counts toward 50% graduate
as E C E 320] and solid-state electronics [such as E C E 335] strongly coursework requirement
encouraged. Repeatable for Credit: No
Requisites: Graduate/professional standing Last Taught: Fall 2023
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: No
Last Taught: Spring 2024
16 Electrical and Computer Engineering (E C E)

E C E/PHYSICS 746 — QUANTUM ELECTRONICS E C E/N E/PHYSICS 749 — COHERENT GENERATION AND
3 credits. PARTICLE BEAMS
3 credits.
Elementary aspects of Lagrange theory of fields and field quantization;
Bose, Fermi and Pauli operators; interaction of fields; quantum theory of Fundamental theory and recent advances in coherent radiation charged
damping and fluctuations; applications to lasers, nonlinear optics, and particle beam sources (microwave to X-ray wavelengths) including free
quantum optics. Knowledge of lasers [such as PHYSICS/E C E 546] and electron lasers, wiggler/wave-particle dynamics, Cerenkov masers,
graduate-level electromagnetics [such as E C E 740 or PHYSICS 721] gyrotrons, coherent gain and efficiency, spontaneous emission, beam
strongly encouraged. sources and quality, related accelerator concepts experimental results and
Requisites: Graduate/professional standing applications.
Course Designation: Grad 50% - Counts toward 50% graduate Requisites: E C E 740
coursework requirement Course Designation: Grad 50% - Counts toward 50% graduate
Repeatable for Credit: No coursework requirement
Last Taught: Fall 2023 Repeatable for Credit: No
Last Taught: Fall 2019
E C E 747 — NANOPHOTONICS
3 credits. E C E/COMP SCI 750 — REAL-TIME COMPUTING SYSTEMS
3 credits.
Optics/photonics at nanometer and micrometer length scales, including
EM waves in dielectrics and metals, computational electromagnetics, Introduction to the unique issues in the design and analysis of computer
waveguides and waveguide coupling, optical resonators, basic systems for real-time applications. Hardware and software support for
nanofabrication techniques, thin-film interference, surface-plasmon guaranteeing timeliness with and without failures. Resource management,
polaritons, localized surface-plasmon resonances, applications of time-constrained communication, scheduling and imprecise computations,
plasmonics, super-resolution imaging, photonic crystals, composite real-time kernels and case studies. Students are strongly encouraged to
materials and metamaterials, metasurfaces. Knowledge of Maxwell's have knowledge of computer architecture (e.g., E C E/COMP SCI 552)
equation and basic ray/wave optics, as would typically be obtained and operating system functions (e.g., COMP SCI 537)
from junior-level or higher electromagnetics or optics courses [such as Requisites: Graduate/professional standing
E C E 320 or E C E 434], is strongly encouraged. Course Designation: Grad 50% - Counts toward 50% graduate
Requisites: Graduate/professional standing coursework requirement
Course Designation: Grad 50% - Counts toward 50% graduate Repeatable for Credit: No
coursework requirement Last Taught: Spring 2024
Repeatable for Credit: No
Last Taught: Fall 2022 E C E 751 — EMBEDDED COMPUTING SYSTEMS
3 credits.
E C E/PHYSICS 748 — LINEAR WAVES
3 credits. Embedded applications, embedded processors and multiprocessors,
embedded system design and simulation, configurable/reconfigurable
General considerations of linear wave phenomena; one dimensional embedded systems, embedded compilers and tool chains, run-time
waves; two and three dimensional waves; wave equations with constant systems, application design and customization, hardware and software co-
coefficients; inhomogenous media; random media. Lagrangian design, low-power design. Knowledge of computer architecture [such as E
and Hamiltonian formulations; asymptotic methods. Knowledge of C E 552] strongly encouraged.
electromagnetics [such as E C E 320 or PHYSICS 321], mechanics [such as Requisites: Graduate/professional standing
M E 340], or vibrations [such as M E 440] strongly encouraged. Course Designation: Grad 50% - Counts toward 50% graduate
Requisites: Graduate/professional standing coursework requirement
Course Designation: Grad 50% - Counts toward 50% graduate Repeatable for Credit: No
coursework requirement Last Taught: Fall 2023
Repeatable for Credit: No
Last Taught: Fall 2022 E C E/COMP SCI 752 — ADVANCED COMPUTER ARCHITECTURE I
3 credits.

Processor design, computer arithmetic, pipelining, multi-operation

processors, vector processors, control units, precise interrupts, main
memory, cache memories, instruction set design, stack machines, busses
and I/O, protection and security. Students are strongly encouraged to
have knowledge of computer architecture (e.g., E C E/COMP SCI 552).
Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: No
Last Taught: Spring 2024
 Electrical and Computer Engineering (E C E) 17

E C E 753 — FAULT-TOLERANT COMPUTING E C E/COMP SCI/E M A/E P/M E 759 — HIGH PERFORMANCE
3 credits. COMPUTING FOR APPLICATIONS IN ENGINEERING
3 credits.
Fault modeling, redundancy techniques and reliability evaluation, error
detecting and correcting codes, self-checking circuits, fault diagnosis, An overview of hardware and software solutions that enable the
software fault tolerance, and case studies. Knowledge of probability [such use of advanced computing in tackling computationally intensive
as E C E 431] and computer architecture [such as E C E/COMP SCI 552] Engineering problems. Hands-on learning promoted through programming
strongly encouraged. assignments that leverage emerging hardware architectures and use
Requisites: Graduate/professional standing parallel computing programming languages. Students are strongly
Course Designation: Grad 50% - Counts toward 50% graduate encourage to have completed COMP SCI 367 or COMP SCI 400 or to
coursework requirement have equivalent experience.
Repeatable for Credit: No Requisites: Graduate/professional standing
Last Taught: Spring 2023 Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
E C E/COMP SCI 755 — VLSI SYSTEMS DESIGN Repeatable for Credit: No
3 credits. Last Taught: Fall 2023

Overview of MOS devices and circuits; introduction to integrated circuit E C E/COMP SCI 760 — MACHINE LEARNING
fabrication; topological design of data flow and control; interactive 3 credits.
graphics layout; circuit simulation; system timing; organizational and
architectural considerations; alternative implementation approaches; Computational approaches to learning: including inductive inference,
design project. E C E 555 or equivalent experience is strongly explanation-based learning, analogical learning, connectionism,
recommended. and formal models. What it means to learn. Algorithms for learning.
Requisites: Graduate/professional standing Comparison and evaluation of learning algorithms. Cognitive modeling and
Course Designation: Grad 50% - Counts toward 50% graduate relevant psychological results.
coursework requirement Requisites: Graduate/professional standing
Repeatable for Credit: No Course Designation: Grad 50% - Counts toward 50% graduate
Last Taught: Spring 2024 coursework requirement
Repeatable for Credit: No
E C E/COMP SCI 756 — COMPUTER-AIDED DESIGN FOR VLSI Last Taught: Spring 2024
3 credits.
E C E/COMP SCI 761 — MATHEMATICAL FOUNDATIONS OF
Broad introduction to computer-aided design tools for VLSI, emphasizing MACHINE LEARNING
implementation algorithms and data structures. Topics covered: 3 credits.
design styles, layout editors, symbolic compaction, module generators,
placement and routing, automatic synthesis, design-rule checking, circuit Mathematical foundations of machine learning theory and algorithms.
extraction, simulation and verification. Students are strongly encourage Probabilistic, algebraic, and geometric models and representations of
to have programming skills and to have taken a course in Digital System data, mathematical analysis of state-of-the-art learning algorithms and
Fundamentals such as E C E/COMP SCI 352. optimization methods, and applications of machine learning. Knowledge of
Requisites: Graduate/professional standing probability [such as MATH/STAT 431 or COMP SCI/E C E 561] and linear
Course Designation: Grad 50% - Counts toward 50% graduate algebra [such as MATH 341 or M E/COMP SCI/E C E 532] is required.
coursework requirement Requisites: Graduate/professional standing
Repeatable for Credit: No Course Designation: Grad 50% - Counts toward 50% graduate
Last Taught: Fall 2023 coursework requirement
Repeatable for Credit: No
E C E/COMP SCI 757 — ADVANCED COMPUTER ARCHITECTURE II Last Taught: Spring 2024
3 credits.

Parallel algorithms, principles of parallelism detection and vectorizing

compilers, interconnection networks, MIMD machines, processor
synchronization, data coherence, multis, dataflow machines, special
purpose processors. Students are strongly encouraged to have knowledge
of computer architecture (e.g., E C E/COMP SCI 552).
Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: No
Last Taught: Spring 2024
18 Electrical and Computer Engineering (E C E)

E C E/COMP SCI 766 — COMPUTER VISION E C E/COMP SCI 782 — ADVANCED COMPUTER SECURITY AND
3 credits. PRIVACY
3 credits.
Fundamentals of image analysis and computer vision; image acquisition
and geometry; image enhancement; recovery of physical scene Security and privacy issues in software, networks, and hardware systems.
characteristics; shape-from techniques; segmentation and perceptual Security vulnerabilities, privacy threats, threats modeling, and mitigation
organization; representation and description of two-dimensional strategies. Privacy issues related to user interaction with devices, online
objects; shape analysis; texture analysis; goal-directed and model- systems, and networks. In addition, a selection of more advanced topics
based systems; parallel algorithms and special-purpose architectures. will be covered. Possible examples include applied cryptography in the
Students are strongly encouraged to have basic proficiency in calculus context of systems, security and privacy policies, user authentication, and
and linear algebra, such as MATH 340, and basic programming such as cyber-physical systems. Builds on prior experiences with one or more of
COMP SCI 300. the following: networking, security, modern machine learning, embedded
Requisites: Graduate/professional standing systems, and mobile computing.
Course Designation: Grad 50% - Counts toward 50% graduate Requisites: Graduate/professional standing
coursework requirement Course Designation: Grad 50% - Counts toward 50% graduate
Repeatable for Credit: No coursework requirement
Last Taught: Spring 2024 Repeatable for Credit: No
Last Taught: Spring 2024
E C E/CBE/MATH 777 — NONLINEAR DYNAMICS, BIFURCATIONS
AND CHAOS E C E 790 — MASTER'S RESEARCH
3 credits. 1-9 credits.

Advanced interdisciplinary introduction to qualitative and geometric Independent work on master's research overseen by a qualified instructor.
methods for dissipative nonlinear dynamical systems. Local bifurcations of Requisites: Declared in Electrical Engineering: Research, M.S. or
ordinary differential equations and maps. Chaotic attractors, horseshoes Electrical Engineering: Power Engineering, M.S.
and detection of chaos. Course Designation: Grad 50% - Counts toward 50% graduate
Requisites: Graduate/professional standing or member of the Pre- coursework requirement
Masters Mathematics (Visiting International) Program Repeatable for Credit: Yes, unlimited number of completions
Course Designation: Grad 50% - Counts toward 50% graduate Last Taught: Spring 2024
coursework requirement
Repeatable for Credit: No E C E 817 — NONLINEAR SYSTEMS
Last Taught: Spring 2016 3 credits.

E C E/B M E/MED PHYS 778 — MACHINE LEARNING IN Modelling nonlinear systems, linearization, equilibria, solution concepts,
ULTRASOUND IMAGING phase plane analysis, stability concepts, Lyapunov methods, oscillations,
3 credits. vector space methods, control system nonlinearities and design. Selected
topics from the following: input-output methods, switching and variable
Concepts and machine learning techniques for ultrasound beamforming structure systems, feedback linearization, and Lyapunov robustness.
for image formation and reconstruction to image analysis and Knowledge of linear systems [such as E C E 717] strongly encouraged.
interpretation will be presented. Key machine learning and deep learning Requisites: Graduate/professional standing
concepts applied to beamforming, compressed sampling, speckle Course Designation: Grad 50% - Counts toward 50% graduate
reduction, segmentation, photoacoustics, and elasticity imaging will be coursework requirement
evaluated utilizing current peer-reviewed publications. Repeatable for Credit: No
Requisites: Graduate/professional standing Last Taught: Spring 2023
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement E C E 821 — OPTIMAL CONTROL AND VARIATIONAL METHODS
Repeatable for Credit: No 3 credits.
Last Taught: Fall 2023
Variational principles in optimization and optimal control, constrained
control and reachability analysis, stability of optimal control, data-driven
methods for optimal control. Knowledge of linear systems [such as
E C E 717] strongly encouraged.
Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: No
Last Taught: Spring 2024
 Electrical and Computer Engineering (E C E) 19

E C E 826 — THEORETICAL FOUNDATIONS OF LARGE-SCALE E C E 845 — TRANSPORT IN SEMICONDUCTOR DEVICES

MACHINE LEARNING 3 credits.
3 credits.
Transport of carriers in electronic devices, starting from the Boltzmann
Mathematical foundations of large-scale machine learning and equation and the quantum mechanical treatment of scattering, and
optimization. Focus on recent texts in machine learning, optimization, and covering applications to devices; transport in 2D structures; modeling of
randomized algorithms, focused on tradeoffs that are driving algorithmic transport; experiments and devices involving hot electrons.
design in this new discipline. These trade-offs revolve around speed of Requisites: E C E 745
convergence, statistical accuracy, robustness, scalability, algorithmic Course Designation: Grad 50% - Counts toward 50% graduate
complexity, and implementation. coursework requirement
Requisites: COMP SCI/E C E 761 Repeatable for Credit: No
Course Designation: Grad 50% - Counts toward 50% graduate Last Taught: Spring 2024
coursework requirement
Repeatable for Credit: No E C E/PHYSICS 848 — NONLINEAR WAVES
Last Taught: Spring 2024 3 credits.

E C E 830 — ESTIMATION AND DECISION THEORY General considerations of nonlinear wave phenomena; nonlinear
3 credits. hyperbolic waves; nonlinear dispersion; nonlinear geometrical optics;
Whitham's variational theory; nonlinear and parametric instabilities;
Estimation and decision theory applied to random processes and signals solitary waves; inverse scattering method. Knowledge of electromagnetics
in noise: Bayesian, maximum likelihood, and least squares estimation; the [such as E C E 320 or PHYSICS 321] or mechanics [such as M E 340]
Kalman filter; maximum likelihood and maximum aposteriori detection; encouraged.
adaptive receivers for channels with unknown parameters or dispersive, Requisites: Graduate/professional standing
fading characteristics; the RAKE receiver; detection systems with learning Course Designation: Grad 50% - Counts toward 50% graduate
features. coursework requirement
Requisites: E C E 730 Repeatable for Credit: No
Course Designation: Grad 50% - Counts toward 50% graduate Last Taught: Spring 2019
coursework requirement
Repeatable for Credit: No E C E/COMP SCI/STAT 861 — THEORETICAL FOUNDATIONS OF
Last Taught: Spring 2019 MACHINE LEARNING
3 credits.
E C E 841 — ANTENNAS
3 credits. Advanced mathematical theory and methods of machine learning.
Statistical learning theory, Vapnik-Chevronenkis Theory, model selection,
Applications of Maxwell's field equations to radiation problems; high-dimensional models, nonparametric methods, probabilistic analysis,
transmission of radio waves; radiation and impedance characteristics of optimization, learning paradigms.
various antennas and arrays. Analysis of complete antenna systems. Requisites: E C E/COMP SCI 761 or E C E 830
Requisites: E C E 740 Course Designation: Grad 50% - Counts toward 50% graduate
Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement
coursework requirement Repeatable for Credit: No
Repeatable for Credit: No Last Taught: Fall 2023
Last Taught: Spring 2023
E C E/MATH/STAT 888 — TOPICS IN MATHEMATICAL DATA
E C E/MATH 842 — TOPICS IN APPLIED ALGEBRA SCIENCE
3 credits. 1-3 credits.

Applied topics with emhasis on algebraic constructions and structures. Advanced topics in the mathematical foundations of data science
Examples include: algebraic coding theory; codes (algebraic-geometric, Requisites: Graduate/professional standing or member of the Pre-
convolutional, low-density-parity-check, space-time); curve and lattice Masters Mathematics (Visiting International) Program
based cryptography; watermarking; computer vision (face recognition, Course Designation: Grad 50% - Counts toward 50% graduate
multiview geometry). coursework requirement
Requisites: Graduate/professional standing or member of the Pre- Repeatable for Credit: Yes, unlimited number of completions
Masters Mathematics (Visiting International) Program Last Taught: Fall 2023
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement E C E 890 — PRE-DISSERTATOR'S RESEARCH
Repeatable for Credit: Yes, unlimited number of completions 1-9 credits.
Last Taught: Spring 2024
Independent work on doctoral research overseen by a qualified instructor.
Requisites: Declared in Electrical Engineering PhD
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: Yes, unlimited number of completions
Last Taught: Spring 2024
20 Electrical and Computer Engineering (E C E)

E C E 901 — SPECIAL TOPICS IN ELECTRICAL AND COMPUTER

ENGINEERING
1-3 credits.

Special advanced topics across Electrical and Computer Engineering. The

topics covered, instructors, and prerequisites all vary with semester and
with section. Particular topics typically reflect state-of-the-art ideas and
research.
Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: Yes, unlimited number of completions
Last Taught: Spring 2024

E C E/N E/PHYSICS 922 — SEMINAR IN PLASMA PHYSICS

0-1 credits.

Current topics in plasma physics.

Requisites: Graduate/professional standing
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: Yes, unlimited number of completions
Last Taught: Spring 2024

E C E 990 — DISSERTATOR'S RESEARCH

1-12 credits.

Independent work on dissertation overseen by a qualified instructor.

Requisites: Declared in Electrical Engineering PhD
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: Yes, unlimited number of completions
Last Taught: Spring 2024

E C E 999 — ADVANCED INDEPENDENT STUDY

1-3 credits.

Directed study projects as arranged with instructor.

Requisites: Consent of instructor
Course Designation: Grad 50% - Counts toward 50% graduate
coursework requirement
Repeatable for Credit: Yes, unlimited number of completions
Last Taught: Fall 2023