Course Catalog

This is the list of courses that the department may offer in a given year. See the current course offerings page for courses offered this semester. Not all courses in the catalog are offered every year. Undergraduate students normally take courses in the 100 – 400 level range, and graduate students normally take courses in the 400 – 500 level range.

Jump to 100 level | 200 level | 300 level | 400 level | 500 level

100 level

ECE 115 Introduction to Computing: Programming Autonomous Vehicles

This course is an introductory course in programming designed for students with minimal or no prior computing experience. Students learn core programming concepts by working with autonomous robotic vehicles, making the learning process hands-on and practical. The curriculum covers essential programming fundamentals including control flow, iteration, functions, recursion, object-oriented programming, and data structures such as lists and arrays. Through integrated lab sessions, students apply these concepts directly by programming real robotic platforms.

200 level

ECE 201 Information Signals (ST)

Signals that carry information, e.g. sound, images, sensors, radar, communication, robotic control, play a central role in technology and engineering. This course teaches mathematical tools to analyze, manipulate, and preserve information signals. We discuss how continuous signals can be perfectly represented through sampling, leading to digital signals. Major focus points are the Fourier transform, linear time-invariant systems, frequency domain, and filtering. We use MATLAB for laboratory exercises. Prerequisite: knowledge of elementary calculus.

ECE 203 Electronic Circuit Design Analysis and Implementation (ST)

Introduction to electronic circuits and systems. Methods of circuit analysis to create functions from devices, including resistors, capacitors, inductors, diodes, and transistors, in conjunction with op-amps. Quantitative focus on DC and higher-frequency signals using linear systems theory with major emphasis on intuition. Students pursue design (using op-amps and micro controllers), simulations (using SPICE), and analysis in labs.

ECE 206 Contemporary Logic Design (also COS 306) (ST)

Introduction of the basic concepts in logic design that form the basis of computation and communication circuits. This course will start from scratch and end with building a working computer on which we will run small programs.

ECE 273 Renewable Engergy and Smart Grids (see ENE 273)

ECE 297 and 298 Sophomore Independent Work

Provides an opportunity for a student to concentrate on a state-of-the-art project in electrical and computer engineering. Topics may be selected from suggestions by faculty members or proposed by the students. The final choice must be approved by the faculty advisor. There is no formal reading list; however, a literature search is a normal part of most projects.

300 level

ECE 301 Designing Real Systems

This course focuses on the science, engineering, and design of the highly integrated systems that dominate many of today's devices. Analysis of systems, sub-systems, and basic principles will be covered, with an emphasis on hardware-software optimization, sampling and digitization, signal and noise, feedback and control, and communication. Prerequisites: 201 and 203.

ECE 302 Robotic and Autonomous Systems Lab

Comprehensive laboratory-based course in electronic system design and analysis. Covers formal methods for the design and analysis of moderately complex real-world electronic systems. Course is centered around a semester-long design project involving a computer-controlled vehicle designed and constructed by teams of two students. Integrates microprocessors, communications, and control. Prerequisites: 201 and 203.

ECE 304 Electronic Circuits: Devices to ICs

The course will cover topics related to electronic system design through the various layers of abstraction from devices to ICs. The emphasis will be on understanding fundamental system-design tradeoffs, related to the speed, precision, power with intuitive design methods, quantitative performance measures, and practical circuit limitations. The understanding of these fundamental concepts will prepare students for a wide range of advanced topics from circuits and systems for communication to emerging areas of sensing and biomedical electronics. Prerequisites: 201 and 203.

ECE 305 Mathematics for Numerical Computing and Machine Learning (also COS 302, SML 305)

This course provides a comprehensive and practical background for students interested in continuous mathematics for computer science. The goal is to prepare students for higher-level subjects in artificial intelligence, machine learning, computer vision, natural language processing, graphics, and other topics that require numerical computation. This course is intended students who wish to pursue these more advanced topics, but who have not taken (or do not feel comfortable) with university-level multivariable calculus (e.g., MAT 201/203) and probability (e.g., ORF 245 or ORF 309).

ECE 308 Electronic and Photonic Devices (ST)

Intro to fundamentals and operations of semiconductor devices and sensors and micro/nano fabrication technologies used to make them. Devices include field-effect transistors, photodetectors and solar cells, light-emitting diodes and lasers. Applications include: computing and microchips, optical transmission of info (the internet backbone), displays and renewable energy. Students will fabricate their own devises in a clean room and test via microprobes. Special emphasis placed on the interplay between the material properties, fabrication capabilities, device performance and ultimate system performance. Prerequisites: MAT103-104 and PHY103-104.

ECE 341 Solid-State Devices

The physics and technology of solid-state devices. Topics include: p-n junctions and two terminal devices, transistors, silicon controlled rectifiers, field effect devices, silicon vidicon and storage tubes, metal-semiconductor contacts and Schottky barrier devices, microwave devices, junction lasers, liquid crystal devices, and fabrication of integrated circuits. Three hours of lectures. Prerequisite: 308 or the equivalent.

ECE 342 Principles of Quantum Engineering

Fundamentals of quantum mechanics and statistical mechanics needed for understanding the principles of operation of modern solid state and optoelectronic devices and quantum computers. Topics covered include Schrödinger Equation, Operator and Matrix Methods, Quantum Statistics and Distribution Functions, and Approximation Methods, with examples from solid state and materials physics and quantum electronics. Prerequisites: (PHY 103 or PHY 105) and (PHY 104 or PHY 106) or EGR 151 and EGR 153. MAT 201 and MAT 202, or EGR 152 and EGR 154.

ECE 345 Introduction to Robotics (also MAE 345, COS 346, ROB345)

Robotics is a rapidly-growing field with applications including unmanned aerial vehicles, autonomous cars, and robotic manipulators. This course will provide an introduction to the basic theoretical and algorithmic principles behind robotic systems. The course will also allow students to get hands-on experience through project-based assignments on quadrotors. In the final project, students will implement a vision-based obstacle avoidance controller for a quadrotor. Topics include motion planning, control, localization, mapping, and vision.

ECE 346 Intelligent Robotic Systems (also COS348, MAE346, ROB346)

Robotic systems are quickly becoming more capable and adaptable, entering new domains from transportation to healthcare. To reliably carry out complex tasks in changing environments and around people, these systems rely on increasingly sophisticated artificial intelligence. This course covers the core concepts and techniques underpinning modern robot autonomy, including planning under uncertainty, imitation and reinforcement learning, multiagent interaction, and safety. The lab component introduces the Robot Operating System (ROS) framework and applies the learned theory to hands-on autonomous driving assignments on 1/16-scale robot trucks. Prerequisite: Multivariable calculus (e.g., MAT 201, 203), linear algebra (e.g., MAT 202, 204), probability (e.g., ORF 309), and programming (e.g., COS 126, ECE 115).. An introduction to robotics and control is helpful (e.g., ROB 345, ECE 302, MAE 433). Programming assignments are in Python.

ECE 351 Foundations of Photonics

This course provides the students with a broad and solid background in electromagnetics, including both statics and dynamics, as described by Maxwell's equations. Fundamental concepts of diffraction theory, Fourier optics, polarization of light, and geometrical optics will be discussed. Emphasis is on engineering principles, and applications will be discussed throughout. Examples include cavities, waveguides, antennas, fiber optic communications, and imaging. Prerequisite: PHY 103 and PHY 104 or equivalent.

ECE 364 Machine Learning for Predictive Data Analytics

Machine learning for predictive data analytics; information-based learning; similarity-based learning; probability-based learning; error-based learning; deep learning; evaluation.

ECE 375 Computer Architecture and Organization (also COS 375)

An introduction to computer architecture and organization. Instruction set design; basic processor implementation techniques; performance measurement; cashes and virtual memory; pipelined processor design; design trade-offs among cost, performance, and complexity. Prerequisite: COS 217.

ECE 368 Introduction to Wireless Communication Systems

Communication systems have become a ubiquitous part of modern life. This course introduces students to the fundamentals of digital communication and wireless systems. Topics include concepts from information, compression, channel, modulation, radio propagation to principles of wireless cellular, and WiFi systems. At the end of the semester, students are expected to gain a deep understanding of the basis of wireless communication systems and the connection between theoretical concepts and real-world systems.

ECE 381 Networks: Friends, Money and Bytes (also COS 381)

This course is oriented around 20 practical questions in the social, economic, and technological networks in our daily lives. How does Google sell ad spaces and rank webpages? How does Netflix recommend movies and Amazon rank products? How do I influence people on Facebook and Twitter? Why doesn't the Internet collapse under congestion, and does it have an Achilles heel? Why does each gigabyte of mobile data cost $10, but Skype is free? How come WiFi is slower at hotspots than at home, and what is inside the cloud of iCloud? In formulating and addressing these questions, we introduce the fundamental concepts behind the networking industry.

ECE 382 Statistical Signal Processing

A wide spectrum of engineering applications require efficient procedures to describe, process, analyze, and infer the signals/data of interest, which are often accomplished by imposing proper statistical models on the objects under consideration. This course introduces the fundamental statistical principles and methods that play a central role in modern signal and information processing. Specific topics include random processes, linear regression and estimation, hypothesis testing and detection, and shrinkage methods. Prerequisites: Linear Algebra and ORF 309.

ECE 396 Introduction to Quantum Computing (also COS 396)

This course will introduce the matrix form of quantum mechanics and discuss the concepts underlying the theory of quantum information. Some of the important algorithms will be discussed, as well as physical systems which have been suggested for quantum computing. Three lectures. Prerequisite: Linear algebra at the level of MAT 202, 204, 217, or the equivalent.

ECE 398 and 399 Junior Independent Work

Provides an opportunity for a student to concentrate on a "state-of-the-art" project in electrical and computer engineering. Topics may be selected from suggestions by faculty members or proposed by the students. The final choice must be approved by the faculty advisor.

400 level

ECE 404/504 Mixed-Signal Circuits and Systems

Discuss design and simulation methodologies for realizing robust analog CMOS circuits implementing major building blocks in A/D conversion. With attention to design specifications, a comprehensive study of single-ended and differential op-amp topologies will be covered with an emphasis on: feedback and stability; linear and non-linear settling; distortion; noise; and voltage swing. Conclude with swtiched-capacitor circuits exploring impact of non-linearity and noise in sampled systems. Design projects using circuit simulators reinforce theoretical concepts. Prerequisite: 304.

ECE 411 Sequential Division Analytics and Modeling (see ORF 411)

ECE 431 Solar Energy Conversion (also MAE 431/ENV 431/EGR 431/ENE 431)

Principles, designs, and economics of solar conversion systems. Quantity and availability of solar energy. Physics and chemistry of solar energy conversion: solar optics; quantum processes; optical excitation; and transport of excitations, electronic, and ionic charge. Methods for conversion: photovoltaics; photoelectrochemistry; photocatalysis; photosynthesis; and solar thermal conversion. Energy collection, transport and storage. Economics: life cycle costing; and societal value of renewable energy. Three one-hour lectures, one preceptorial. Prerequisites: MAT 104, PHY 104 or EGR 153, and CHM 207.

ECE 432 Information Security (also COS 432)

Security issues in computing, communications, and electronic commerce. Goals and vulnerabilities; legal and ethical issues; basic cryptology; private and authenticated communication; electronic commerce; software security; viruses and other malicious code; operating system protection; trusted systems design; network security; firewalls; policy, administration and procedures; auditing; physical security; disaster recovery; reliability; content protection; privacy. Prerequisites: COS 217 and 226.

ECE 434 Machine Learning Theory (also COS 434)

The course covers basic theories of modern machine learning: 1. statistical learning theory: generalization, uniform convergence, Rademacher complexity, VC theory, reproducing Hilbert kernel space and their applications on simple classification/regression models; 2. optimization theory: gradient descent, stochastic gradient descent and their convergence analyses for convex functions, nonconvex functions 3. deep learning theory: basic approximation, optimization and generalization results for deep neural networks; 4. reinforcement learning theory: MDP, Bellman equations, planning, and sample complexity results for value iteration/Q-learning.

ECE 435/535 Machine Learning and Pattern Recognition

This course is an introduction to the theoretical foundations of machine learning. A variety of classical and recent results in machine learning and statistical analysis are discussed, including: classification, regression, regularization, optimization, gradient descent, neural networks, convolutional networks, and reinforcement learning.

ECE 441 Solid-State Physics I (also ENE 441)

An introduction to the properties of solids. Theory of free electrons--classical and quantum. Crystal structure and methods of determination. Electron energy levels in a crystal: weak potential and tight-binding limits. Classification of solids--metals, semiconductors, and insulators. Types of bonding and cohesion in crystals. Lattice dynamics, phonon spectra, and thermal properties of harmonic crystals. Three hours of lectures. Prerequisite: 342, or PHY 208 and 305, or equivalent.

ECE 442 Solid-State Physics II

Electronic structure of solids. Electron dynamics and transport. Semiconductors and impurity states. Surfaces and interfaces. Dielectric properties of insulators. Electron-electron, electron-phonon, and phonon-phonon interactions. Anharmonic effects in crystals. Magnetism. Superconductivity. Alloys. Three hours of lectures. Prerequisites: 441 or equivalent.

ECE 445 Solid-State Electronic Devices

The physics and technology of solid-state electronic devices. Covers electronic structure of semiconductors, energy bands and doping, followed by discussion of carrier transport by drift and diffusion and recombination/generation. Detailed analysis of p-n junctions, bipolar transistors and field effect transistors. Survey of a wide range of devices, including photodetectors, solar cells, light-emitting diodes and semiconductor lasers, highlighting contemporary concepts such as thin film electronics and 2D semiconductors. Prerequisites: Basic E&M and calculus.

ECE 449/549 Micro-Nano Fabrication and Thin Film Processing (also MSE 449)

This course will investigate the technology and underlying science of micro-and nano-fabrication, which are the methods used to build billions of electronic and optoelectronic devices on a chip, as well as general small sensors and actuators generally referred to as micro-electromechanical systems (MEMS). The general approach involves deposition modification, and patterning of layers less than one-micrometer thick, hence the generic term 'thin-film' processing. Topics to be covered film deposition and growth via physical and chemical vapor deposition, photolithography, pattern transfer, plasma-processing, ion-implantation, and vacuum science.

ECE 452 Biomedical Imaging

This course gives a general introduction to biological and biomedical imaging. Topics covered include basic imaging theory, microscopy, tomography, and imaging through tissue. Both physical and computational imaging will be covered, across a variety of different modalities (including visible light, x-ray, MRI, and ultrasound). The gaps between current technology and limits suggested by information theory will be discussed.

ECE 453 Optical and Quantum Electronics

Fundmentals of light-matter interactions, waveguides and resonators, nonlinear optics and lasers.

ECE 455 Optical and Photonic Systems for Environmental Sensing (also CEE 455/MAE 455/MSE 455)

This class will teach you about optical and photonic sensing technologies and their applications to environmental monitoring. The course will contain elements of atmospheric science and Earth observation, fundamentals of optics, photonics and laser physics, as well as a survey of modern optical and spectroscopic sensing applications. In this course students will be asked to prepare two oral presentations and there will be three laboratory assignments focused on fundamentals of optical sensing.

ECE 456 Quantum Optics (also PHY456)

Semiclassical field theory of light-matter interactions. Quantum theory of light, vacuum fluctuations and photons. Quantum states and coherence properties of the EM field, photon counting and interferometry. Quantum theory of light-matter interactions, Jaynes-Cummigns (JC) model. Physical realizations of JC model, case study:circuit QED. Quantum theory of damping. Resonance fluorescence. Coupled quantum non-linear systems. Prerequisite: 453.

ECE 457 Experimental Methods in Quantum Computing

This course aims to introduce students to the basics of experimental quantum information processing. Students will gain hands-on experience with several qubit platforms, including single photons, nuclear spins (NMR), electron spins (NV centers in diamond), and superconducting qubits. Additionally, students will learn data analysis and signal processing techniques relevant for a wide range of quantum computing platforms. Prerequisite: Quantum mechanics (PHY 305 and/or ECE 342). ECE/COS 396 is recommended but not required.

ECE 458/558 Photonics and Light Wave Communications

ECE 461 Design with Nanotechnologies

Introduction to nanotechnologies; threshold logic/majority logic and their applications to RTDs, QCA and SETs; nanowire based crossbars and PLAs; carbon nanotube based circuits; double-gate CMOS-based circuits; reversible logic for quantum computing; non-volatile memory; nanopipelining; testing; and defect tolerance. Two 90-minute lectures. Prerequisite: ELE 203 and 206.

ECE 462/562 Design of Very Large-Scale Integrated (VLSI) Systems (also COS 462)

Analysis and design of digital integrated circuits using deep sub-micron CMOS technologies as well as emerging and post-CMOS technologies (Si finFETs, III-V, carbon). Emphasis on design, including synthesis, simulation, layout and post-layout verification. Analysis of energy, power, performance, area of logic-gates, interconnect and signaling structures.

ECE 463 Wireless Networks (see COS 463)

ECE 464 Embedded Computing

Introduction to embedded computing, cyberphysical systems and Internet-of-Things: basic concepts; reliability, availability, power/energy consumption, security. Finite-state machines. Sensors and actuators. Embedded processors. Performance/power analysis. Real-time systems. System-on-chip architectures. Hardware-software co-design. High-level synthesis. Low-power embedded system design. Prerequisite: 206.

ECE 469 Human-Computer Interface Technology (see COS 436)

ECE 470 Principles of Blockchains (also COS 470)

Blockchains are decentralized digital trust engines that are the underlying technology behind Web3, a loosely defined denotation of the Internet architecture in the years to come, including decentralization of the platform economy of the modern Internet (Web2). In this course, we conduct a full-stack study of blockchains, viewing them as a whole integrated computer system involving networking, incentives, consensus, data structures, cryptography and memory management. The course uses the Bitcoin architecture as a basis to construct the foundational design and algorithmic principles of blockchains. Prerequisites: The basic prerequisites are a maturity with algorithms (COS 226), probability and computer systems (COS 316). Experience with computer security (COS/ECE 432) and networking (COS/ECE 461) will be helpful.

ECE 472 Architecture for Secure Computers and Smartphones

We study how to design secure processors, cashes and systems for secure computers and smartphones. Topics include hardware-enhanced secure execution environments, secure cache architectures resilient to side and covert channel attacks, new processor designs for defeating speculative and timing attacks, solving security problems using machine/deep learning, smartphone security architecture, designing a deep learning engine for smartphone security and attacks on deep learning systems. The goal is to train computer architects to design secure computers, and software/security students to understand the importance of hardware in a secure system.

ECE 475/575 Computer Architecture (also COS 475)

An in-depth study of the fundamentals of modern computer processor and system architecture. Students will develop a strong theoretical and practical understanding of modern, cutting-edge computer architectures and implementations. Studied topics include: Instruction-set architecture and high-performance processor organization including pipelining, out-of-order execution, as well as data and instruction parallelism. Cache, memory, and storage architectures. Multiprocessors and multicore processors. Coherent caches. Interconnection and network infrastructures. Prerequisite: ECE 375/COS 375 and ECE 206/COS 306 (or familiarity with Verilog).

ECE 477 Smart Healthcare

Introduction to smart healthcare; health decision support system; wearable medical sensors and deep neural network based disease detection; continual learning based multi-headed neural networks for multi-disease detection; interpretability through differentiable logic networks; interpretability through conformal predictions; medical images and convolutional neural network based disease detection; natural language processing for healthcare; foundation models for healthcare; counterfactual reasoning based personalized medical decision-making.

ECE 480 fMRI Decoding: Reading Minds Using Brain Scans (also NEU 480, PSY 480)

How can we decode what people are thinking by looking at their brain scans? Over the past several years, researchers have started to address this question by applying sophisticated pattern-classification algorithms to patterns of functional MRI data, with the goal of decoding the information that is represented in the subject's brain at a particular point in time. In lectures, students will learn about cutting-edge techniques for finding meaningful patterns in large, noisy datasets; in weekly computer labs, students will use these techniques to gain insight into fMRI datasets.

ECE 481/581 Principles Power Electronics (Also ENE 481)

Power electronics circuits are critical building blocks in a wide range of applications, ranging from mW-scale portable devices, W-scale telecom servers, kW-scale motor drives, to MW-scale solar farms. This course is a design-oriented course and will present fundamental principles of power electronics. Topics include: 1) circuit elements;2) circuit topology; 3) system modeling and control; 4) design methods and practical techniques. Numerous design examples will be presented in the class, such as solar inverters, data center power supplies, radio-frequency power amplifiers, and wireless power transfer systems. Prerequisite 203. 308 recommended only.

ECE 482 Digital Signal Processing

The lectures will cover: (1) Basic principles of digital signal processing. (2) Design of digital filters. (3) Fourier analysis and the fast Fourier transform. (4) Roundoff errors in digital signal processing. (5) Applications of digital signal processing.

ECE 486 Transmission and Compression of Information (also APC 486)

Introduction to digital communication systems and networks, introductory information and coding theory, digital modulation, layered architecture concept of networks, introductory traffic and queuing theory, local area networks and media access control, error control in networks, switching and multiplexing, ATM (asynchronous transfer mode) in B-ISDN (broadband integrated services digital networks). Three hours of lectures. Prerequisites: ORF 309.

ECE 488 Fundamental Image Processing: From Mars to Hollywood with a Stop at the Hospital

We cover the world of digital imaging, from how digital cameras form images to how special effects are used in Hollywood movies and how the Mars Rover sends photographs across millions of miles of space. The course starts by looking at how the human visual system works and then teaches the engineering, mathematics, and CS that makes digital images work. We will learn algorithms used for adjusting images, explore JPEG and MPEG standards for encoding and compressing video images, and go on to learn about image segmentation, noise removal and filtering. We will end with image processing techniques used in medicine and special projects.

ECE 491 High-Tech Entrepreneurship (also EGR 491/ORF 491)

Designed for seniors in the sciences and engineering who are interested in starting a high-tech company early in their careers or who want to join emerging technology companies after graduation. The course is open to any student with a strong background in technology who is interested in launching new enterprises. Two 90-minute lectures.

ECE 498 Senior Thesis I (Year-Long) Fall

The senior thesis (498-499) is a year-long project in which students complete a substantial piece of research and scholarship under the supervision and advisement of a Princeton faculty member in science, engineering, or a technical field. The work requires sustained investment and attention throughout the academic year.

ECE 499 - Senior Thesis II (Year-Long)

500 level

ECE 501/EGR 501 Responsible Conduct in Research

This course educates the graduate student of engineering in the responsible conduct of research. The lectures provide theoretical background information as well as case studies about ethics in day-to-day research situations, in publishing and peer-review, in student-advisor relationships, in collaborative research, as well as in the big picture and considerations of long-term impact. The students are provided with resources to consult in ethical questions. In small-group discussions in departmental and research field-specific precepts, the theoretical concepts are made relevant to the individual students situations.

ECE 511 Quantum Mechanics with Applications

This course covers the principles of quantum mechanics, including applications of relevance to students in applied physics, materials science and engineering. Topics include the concept of Hilbert Spaces, Schrodinger and Heisenberg Representations, Bound State and scattering problems in one, two and three dimensions, consequences of symmetry, Angular momentum algebra, Approximation methods for stationary states, Many-body systems, Quantum statistics and applications in solid state and quantum optics. Time dependent Perturbation Theory and/or Second Quantization and Electromagnetic Field are covered if time permits.

ECE 513/MSE 531 Introduction to Nano/Microfabrication

Introduces to students the basic technologies and knowledge of nano/microfabrication, and give them hands-on experiences in making nano/microstructures and handling sophisticated equipment. The course consists of four one-hour lectures (one per week), seven three-hour labs (one lab per week), and three experiments. Each student begins with a bare silicon wafer and ends with micro-structures consisting of resistors, capacitors, diodes, and transistors. Students learn and perform wafer cleaning, thermal oxidation of thin films, dopant diffusion, photolithography, chemical etching, metal thin-film evaporation, and related.

ECE 514 Extramural Research Internship

Full-time research internship at a host institution, to perform scholarly research relevant to student's dissertation work. Research objectives will be determined by advisor in conjunction with outside host. A mid-semester progress review and a final paper are required. Enrollment limited to post-generals students for up to two semesters. Special rules apply to international students regarding CPT/OPT use. Students may register by application only.

ECE 515 Extramural Summer Project

Summer research project designed in conjunction with the student's advisor and an industrial, NGO, or government sponsor, that will provide practical experience relevant to the student's research area. Start date no earlier than June 1. A research project and sponsor's evaluation are required.

ECE 516 Automated Reasoning about Software

An introduction to algorithmic techniques for reasoning about software. Basic concepts in logic-based techniques including model checking, invariant generation, symbolic execution, and syntax-guided synthesis; automatic decision procedures in modern solvers for Boolean Satisfiability (SAT) and Satisfiability Modulo Theory (SMT); and their applications in automated verification, analysis, and synthesis of software. Emphasis on algorithms and automatic tools.

ECE 518 Selected Topics in Computer Engineering and Information Sciences and Systems

This course introduces first year graduate students to the research of the faculty in the area of Computer Engineering and Information Sciences and Systems. It helps first year graduate students find a research advisor.

ECE 519 Selected Topics in Solid-State Electronics: Advanced Topics in electronic and Optoelectronic Materials and Devices

Introduction to the topics and methods of research in electronic materials and devices, providing an overview of current research of the faculty in electronic materials and devices, and in optical and optoelectronic engineering.

ECE 520 Mathematics of Data Science

This is a graduate-level course covering various aspects of mathematical data science, particularly for large-scale problems. It covers the mathematical foundations of several fundamental learning and inference problems, including clustering, spectral methods, tensor decomposition, graphical models, large-scale numerical linear algebra, matrix concentration inequalities, sparse recovery and compressed sensing, low-rank matrix factorization, shallow neural nets, etc. Both convex and nonconvex approaches are discussed. The course focuses on designing algorithms that are effective in both theory and practice.

ECE 521/MAE 547 Linear System Theory

This course covers the fundamentals of linear system theory. Various topics important for further study in dynamic systems, control and communication and signal processing are presented.

ECE 523/MAE 548 Nonlinear System Theory

A study of the mathematical techniques found useful in the analysis and design of nonlinear systems. Topics include stability and qualitative behavior of differential equations, functional analysis and input/output behavior of systems, and "modern'' nonlinear system theory, which uses both geometric and algebraic techniques. Prerequisite: 521.

ECE 524 Foundations of Reinforcement Learning

The course is a graduate level course, focusing on theoretical foundations of reinforcement learning. It covers basics of Markov Decision Process (MDP), dynamic programming based algorithms, policy optimization, planning, exploration, as well as information theoretical lower bounds. Various advanced topics are also discussed, including off-policy evaluation, function approximation, partial observable MDP and deep reinforcement learning. This course puts special emphases on the algorithms and their theoretical analyses. Prior knowledge on linear algebra, probability theory, and stochastic process is required.

ECE 525 Random Processes in Information Systems

Fundamentals of probability and random processes and their applications to information sciences and systems. The course examines sequences of random variables and convergence; stationarity and ergodicity; second-order properties and estimation; Poisson and renewal processes; and Markov processes.

ECE 526 Digital Communications and Systems

Digital communications and data transmission. Topics include source coding, signal encoding, representation, and quantization; methods of modulation, synchronization, and transmission; optimum demodulation techniques; and communication through band-limited and random channels.

ECE 527 Selected Topics in Signal Processing

Topics of current interest on digital signal processing algorithms and their implementation, including floating point arithmetic roundoff errors, fast transform algorithms, multirate and multidimensional signal processing, spectral estimation, and adaptive signal processing. Prerequisites: 482 and 525 or the equivalent.

ECE 528 Information Theory

An exploration of the Shannon theory of information, covering noiseless source coding theory of ergodic sources and channel coding theorems, including channels with memory, multiple-access, and Gaussian channels.

ECE 529 Theory/Phys Foundations/Random Processes

A systematic treatment of the mathematical properties of stochastic processes. The course explores fundamental concepts and general properties; convergence, second-order processes, and processes of orthogonal increments; and Wiener theory. It examines Brownian motion and stochastic integrals and processes with independent increments. Markov processes and diffusion equations and stochastic differential equations are studied. There are applications in detection, estimation, and stochastic control. Prerequisite: 485 or 525 or the equivalent.

ECE 530 Theory of Detection and Estimation and Learning

Hypothesis testing; detection and estimation of signals in noise; detection of signals with unknown parameters; prediction and filtering of stationary time series; detection of stochastic signals; and nonparametric and robust techniques. Prerequisite: 525 or the equivalent.

ECE 532 Safety-Critical Robotic Systems

The course covers the mathematical foundations of dynamical system safety analysis and modern algorithmic approaches for robotic decision making in safety-critical contexts. The focus is on safe robot learning, multiagent systems, and interaction with humans, paying special attention to uncertainty and the reality gap between mathematical models and the physical world.

ECE 533/MAE 575 Data Assimilation

This course covers the theory and numerical algorithms of nonlinear filtering and smoothing, starting with the discrete-time linear Gaussian case and advancing through the general continuous-time nonlinear non-Gaussian case. Variants of Kalman and ensemble methods will be covered with derivations and sketches of important proofs. A review of the necessary elements from probability and stochastic processes is included. Following the theory, numerical algorithms are regularly demonstrated on a suite of problems that include aerospace and geoscience applications.

ECE 535 Machine Learning and Pattern Recognition

An introduction to the theoretical foundations of machine learning and pattern recognition. Topics include Bayesian pattern classification; parametric methods; nearest neighbor classification; Kernel methods; density estimation; VC theory; neural networks; stochastic approximation. Prerequisites: ELE525 or the permission of the instructor.

ECE 538 and 539 Special Topics in Data and Information Sciences and Systems

Advanced studies in selected areas in signal processing, communication and information theory, decision and control, and system theory. Emphasis on recent developments and current literature. Content varies from year to year according to the instructor's and students' interests.

ECE 540 Organic Materials for Photonics & Electronics

An introduction to organic materials with application to active electronic and photonic devices. Basic concepts and terminology in organic materials, and electronic and optical structure-property relationships are discussed. Charge transport, light emission and photoinduced charge transfer are examined. Finally, archetype organic devices as light emitting diodes, photodetectors and transistors are described.

ECE 541 Quantum Material Spectroscopy

This course introduces students to state-of-the-art techniques in spectroscopy and imaging of solid-state quantum materials, including material systems for quantum information processing, topological and 2D materials, and strongly correlated systems. Lectures focus on both theoretical and practical understanding of the primary materials spectroscopy tools, complemented by a literature survey of current topics. Particular emphasis is placed on novel techniques such as nanoscale quantum sensing, low dimensional systems, spectroscopy of nanostructures, and understanding sources of decoherence in quantum information processing platforms.

ECE 542 Solid State Physics II

This is a second-semester course with an emphasis on topics of interest to applied physicists and material scientists (e.g., semiconductors, optical properties and dielectrics.) It builds upon the material covered in ELE 441 and extends it to multiple areas. These include electronic structure of solids, electron dynamics and transport, semiconductors and impurity states, electron-electron, electron-phonon, and phonon-phonon interactions, anharmonic effects in crystals, dielectric properties of insulators, magnetism, superconductivity. Prerequisites of ELE 441 or PHY 405 or permission of instructor.

ECE 544 Physics & Technology of Low-Dimensional Electronic Structures

A broad overview of materials science and physics of low-dimensional electronic structures will be presented. Emphasis is on the fabrication and physics of high-mobility carrier systems in modulation-doped structures. Examples include two-dimensional, one-dimensional (quantum wire), and zero-dimensional (quantum dot) systems.

ECE 545 Electronic Devices

The physics and technology of electronic devices; junctions, junction transistors, and field-effect transistors; and MOS; and integrated circuits, and special microwave devices.

ECE 546 Subwavelength Nanophotonics and Plasmonics

Classical and quantum mechanical theories for absorption and dispersion. The optical properties are derived from knowledge of electronic band structure of solids, including excitons and effects of external perturbations; the influence of doping, disorder, and reduced dimensionality; bulk and surface polaritons; nonlinear optical processes, and transient and irreversible phenomena. An overview of major measurement techniques is included.

ECE 547 Selected Topics in Solid-State Electronics

One or more advanced topics in solid-state electronics. Contents vary from year to year. Recent topics have included: electronic properties of doped semiconductors, physics and technology of nanostructures, and organic materials for optical and electronic device application.

ECE 549/MSE 549 Micro-Nanofabrication and Thin-Film Processing

This course investigates the technology and underlying science of micro-and nano-fabrication, which are the methods used to build billions of electronic and optoelectronic devices on a chip, as well as general small sensors and actuators generally referred to as micro-electromechanical systems (MEMS). The general approach involves deposition, modification, and patterning of layers less than one-micrometer thick, hence the generic term "thin-film" processing. Topics covered: film deposition and growth via physical and chemical vapor deposition, photolithography, pattern transfer, plasma-processing, ion-implantation, and vacuum science.

ECE 550 Laser Spectroscopy: New Technologies and Applications

The course focuses on various aspects of laser spectroscopic sensing. Topics include physical principles of atomic and molecular spectroscopy, fundamentals of high resolution lasers spectroscopy, spectroscopic measurement techniques and instrumentation, laser sources and practical applications of spectroscopic sensing. Example applications of laser spectroscopy to chemical analysis and trace gas detection in fundamental science, industrial and environmental monitoring and medical diagnostics are discussed.

ECE 551 Theory and Application of Photonic Devices

A foundation in the principle of operation of semiconductor-based photonic devices. Topics include how system requirements have an impact on device design, semiconductor laser diode and photodiode physics, modulators, and optoelectronic- and photonic-integrated circuits.

ECE 552 Advanced Microscopy and Image Processing for Living Systems

For the past three decades have witnessed an explosion of new forms of optical microscopy that allows us to study living systems with unprecedented details. This course aims to cut through the confusion of the wide array of new imaging methods by offering both a unified theoretical framework and practical descriptions of the pros and cons of each. In addition, this course will also explore advances in computational tools, especially recent advances in AI, for image visualization and quantification.

ECE 554 Nonlinear Optics

A general introduction to nonlinear optics, including harmonic generation, parametric amplification and oscillation, electro-optic effects, photorefractive materials, nonlinear spectroscopy, and nonlinear imaging.

ECE 558 Photonics and Lightwave Communications

This course provides an introduction to the state-of-the-art in photonic technology and systems, focusing on high performance fiber-optic telecommunication systems of silicon photonics. The basic physical principles and performance characteristics of optical fibers, lasers, detectors, optical amplifiers and dispersion management will be discussed. The design and performance analysis of photonic systems are presented. There are four participatory lab demonstrations exposing students to the components in a fiber optic communication link. In lieu of a final exam, students do a lab project or term paper, and class presentation.

ECE 559 Photonic Systems

Rapid advances in photonic chip integration has enabled the development of increasingly sophisticated photonic systems for communications and computing. This course covers: Silicon photonic chip design; photonic system fundamentals, noise characteristics & performance requirements; photonic system design & technology, based on off-the-shelf components & integrated silicon photonic platforms; photonic systems applications, including communication networks & intra-chip interconnects, analog signal processors for cyber-physical systems & cryptography, and neuromorphic computing for nonlinear optimization & real-time signal analysis.

ECE 560 Fundamentals of Nanophotonics

Introduction to theoretical techniques for understanding and modeling nanophotonic systems, emphasizing important algebraic properties of Maxwell's equations. Topics covered include Hermitian eigensystems, photonic crystals, Bloch's theorem, symmetry, band gaps, omnidirectional reflection, localization and mode confinement of guided and leaky modes. Techniques covered include Green's functions, density of states, numerical eigensolvers, finite-difference and boundary-element methods, coupled-mode theory, scattering formalism, and perturbation theory. The course explores application of these techniques to current research problems.

ECE 562 Design of Very Large-Scale Integrated (VLSI) Systems

ECE 567/PHY 567 Advanced Solid-State Electron Physics

Electron localization in disordered structures - Anderson model and scaling theory of localization; correlated electron systems - Hubbard model, Mott transition; metal-insulator transitions in correlated and disordered materials; quantum Hall effect - integer and fractional; and quantum phase transitions.

ECE 568 Implementations of Quantum Information

This course provides an overview of experimental approaches to quantum information processing and quantum computing. We discuss the basic principles of quantum computing to understand the physical requirements, and then survey current research on implementing quantum information processing in various physical systems, in part by reading recent experimental literature. Specific topics covered include gate-based and adiabatic quantum computing, topologically protected quantum architectures, as well as several physical qubit systems: trapped ions/atoms, superconducting circuits, and electron and nuclear spins in solids.

ECE 569 Quantum Information and Entanglement

Quantum information theory is a set of ideas and techniques that were developed in the context of quantum computation but now guide our thinking about a range of topics from black holes to semiconductors. This course introduces the central ideas of quantum information theory and surveys their applications. Topics include: quantum channels and open quantum systems; quantum circuits and tensor networks; a brief introduction to quantum algorithms; quantum error correction; and applications to sensing, many-body physics, black holes, etc.

ECE 571 Deep Learning Networks

The course explores basic and advanced topics on MLP (NN1.0), CNN (NN2.0), and NAS (Neural Architecture Search) for deep learning. Basic topics: Sigmoid/ReLU activations, dropout, regularization, and BP learning of net's parameters. More advanced: (1) unifying MLP and CNN learning methods, (2) unifying classification and regression applications, and (3) balancing training and generalization, and (4) applying input/output residual learning to mitigate curse of depth. This ultimately leads to an architecture engineering system (XNAS), a combination of joint parameter/structure X-learning and reinforcement learning paradigms.

ECE 572 Architectures for Secure Computers and Smartphones

We study how to design secure processors, caches and systems for secure computers and smartphones. Topics include hardware-enhanced secure execution environments, secure cache architecture resilient to side and covert channel attacks, new processor designs for defeating speculative and timing attacks, solving security problems using machine/deep learning, smartphone security architecture, designing a deep learning engine for smartphone security and attacks on deep learning systems. The goal is to train computer architects to design secure computers and software/security students to understand the importance of hardware in a secure system.

ECE 574 Security and Privacy in Computing and Communications

As our society transitions towards an information-driven paradigm, concerns about security and privacy of computing and communication have come to a forefront. This course exposes students to foundational principles and mechanisms that enable security and privacy in computing and communications. In addition, we study the interdisciplinary dimension of security and privacy by exploring its intersections with machine learning, information theory, computer architecture and formal methods.

ECE 575 Computer Architecture

An in-depth study of the fundamentals of modern computer processor architecture. Students develop a strong theoretical and practical understanding of the design of modern, cutting-edge, computer architectures and implementations. Studied topics include: instruction-set architecture and high-performance processor organization including pipelining, out-of-order execution, as well as data and instruction parallelism, Cache, memory and storage architectures. Multiprocessors and multicore processors. Coherent caches, interconnection and network infrastructures.

ECE 580/COS 580 Advanced Topics in Computer Engineering

Selected research topics in computer engineering. Emphasis is on new results and emerging areas. (More detailed outlines are contained in the booklet Course Outlines, issued by the department each year.)

ECE 581 Principles of Power Electronics

This course presents fundamental principles and design techniques of power electronics. Topics include 1) circuit elements: semiconductor devices, magnetic components, and filters; 2) circuit topology: canonical switching cells of power converters, inverters, rectifiers, dc-dc converters and ac-dc converters; 3) system modeling and control: small signal modeling, feedback control and system stability analysis; 4) design methods: gate drive, magnetic optimization, electromagnetic interference and thermal management. Numerous practical design examples are presented in class.

ECE 582 Wireless and High Speed Integrated Circuits and Systems

This course aims to cover the fundamentals of the wireless and high-speed integrated circuits for future wireless technology. We cover analysis and design of high-speed and wireless ICs that enables modern wireless communication across device-circuits-system level abstractions. The understanding of these fundamental concepts prepares students for a wide range of advanced topics from circuits and systems for communication to emerging areas of sensing and biomedical electronics.

ECE 584 Advanced Wireless Systems

This course focuses on advanced and merging topics in wireless systems. It covers millimeter-wave and terahertz communications, reconfigurable radio environments, wireless sensing, communications for robotics, multiple-input multiple output systems, visible light communication, 5G/6G, wireless security. The students develop skills to understand and critically evaluate research advances related to wireless systems. This course is half-lecture half-debate. We first cover the principles of wireless systems and then students read and debate over recent papers published at flagship conferences. The students learn to critically analyze research.

ECE 585 Parallel Computation

The class reads seminal papers on different parallel programming models and parallel computer architectures. In addition, we explore different parallel programming models via programming assignments. Finally the course culminates in a project where students create a research-grade experiment and write a full length conference-style paper. One of the goals of this class is to get students introduced to writing a complete conference style computer architecture/CS paper.

ECE 597 and 598 Electrical and Computer Engineering Master's Project

Under the direction of a faculty member, each student carries out a master's-level project and presents their results. For M. Eng. student, 597, fall term; 598 spring term.