Electrical & Computer Eng
- COS 302/SML 305/ECE 305: Mathematics for Numerical Computing and Machine LearningThis 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). See "Other Information"
- COS 375/ECE 375: Computer Architecture and OrganizationAn introduction to computer architecture and organization. Instruction set design; basic processor implementation techniques; performance measurement; caches and virtual memory; pipelined processor design; design trade-offs among cost, performance, and complexity.
- COS 432/ECE 432: Information SecurityHow to secure computing systems, communications, and users. Basic cryptography; private and authenticated communication; software security; malware; operating system protection; network security; web security; physical security; cryptocurrencies and blockchains; privacy and anonymity; usable security; economics of security; ethics of security; legal and policy issues.
- COS 516/ECE 516: Automated Reasoning about SoftwareAn 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 115: Introduction to Computing: Programming Autonomous VehiclesThis course is an introductory course in programming and computing concepts for engineering students who have little or no experience in computing and programming and are interested in learning programming in the context of a robotic autonomous vehicle system. Introduction to fundamental programming concepts: control flow, iteration, abstraction, sub-routines, functions, recursion, lists and arrays. This course is tightly integrated with a real robotic platform: an autonomous Unmanned Aerial Vehicle which the students will program and fly in lab as they learn programming. Significant emphasis will be placed on building good debugging skills.
- ECE 206/COS 306: Contemporary Logic DesignIntroduction to the basic concepts in logic design that form the basis of computation and communication circuits. Logic gates and memeory elements. Timing methodologies. Finite state systems. Programmable logic. Basic computer organization.
- ECE 297: Sophomore Independent WorkProvides an opportunity for a student to concentrate on a state-of-the-art project in electrical 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.
- ECE 302: Robotic and Autonomous Systems LabComprehensive, 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.
- ECE 308: Electronic and Photonic DevicesIntro to fundamentals and operations of semiconductor devices and sensors and the micro/nano fabrication technologies used to make them. The devices include field-effect transistors, photodetectors and solar cells, light-emitting diodes and lasers. Applications to be discussed 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 them via microprobes. Special emphasis will be placed on the interplay between the material properties, fabrication capabilities, device performance and ultimate system performance.
- ECE 341: Solid-State DevicesThe physics and technology of solid state devices. Review of 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.
- ECE 351: Foundations of Modern OpticsThis 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.
- ECE 364: Machine Learning for Predictive Data AnalyticsMachine learning for predictive data analytics; data to insight to decisions; data exploration; information-based learning; similarity-based learning; probability-based learning; error-based learning; evaluation; case studies.
- ECE 396/COS 396: Introduction to Quantum ComputingThis 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.
- ECE 397: Junior Independent WorkProvides an opportunity for a student to concentrate on a "state-of-the-art" project in electrical 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.
- ECE 434/COS 434: Machine Learning TheoryThe 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: Machine Learning and Pattern RecognitionThe 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, included: Bayesian classification, regression, regularization, sparse regression, support vector machines, kernels, neural networks and gradient descent.
- ECE 441/ENE 441: Solid-State Physics IAn 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.
- ECE 453: Optical and Quantum ElectronicsFundmentals of light-matter interactions, waveguides and resonators, nonlinear optics and lasers.
- ECE 458: Photonics and Light Wave CommunicationsThis 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 will be presented. There will be 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 462/COS 462: Design of Very Large-Scale Integrated (VLSI) SystemsAnalysis 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 472: Architectures for Secure Computers and SmartphonesOur goal is to integrate security into the design of all computers. We discuss smartphone architecture and the fundamental security concepts needed to provide smartphone security. We also discuss modern computer architecture in edge-cloud systems, and how they can be attacked, e.g., by cache side-channel attacks, and speculative execution attacks like Spectre and Meltdown. We discuss hardware defenses like secure caches, secure speculation, trusted execution environments, self-protecting data, and improving security with deep-learning. Students will learn secure hardware design strategies and how to apply fundamental security principles.
- ECE 481/ENE 481: Principles of Power ElectronicsPower 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.
- ECE 497: Senior Independent WorkSenior Thesis Course. The student has the opportunity to do a self driven project by proposing a topic and finding a faculty member willing to supervise the work, or, the student may do a project in conjunction with a faculty member's research. A second reader will be required for both the midterm report and final thesis report. Students will be required to enroll in ECE 498 in the spring.
- ECE 497R: Senior Independent Work-ResubmissionNo description available
- ECE 498: Senior Independent WorkProvides an opportunity for a student to concentrate on a "state-of-the-art" project in electrical engineering. A student may propose a topic and find a faculty member willing to supervise the work. Or the student may select a topic from lists of projects obtained from faculty and off-campus industrial researchers, subject to the consent of the faculty advisor.
- ECE 511: Quantum Mechanics with ApplicationsThis 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 514: Extramural Research InternshipFull-time research internship at a host institution, to perform scholarly research relevant to student's dissertation work. Research objectives are 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 518: Selected Topics in Computer Engineering and Information Sciences and SystemsThis 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 DevicesIntroduction 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 535: Machine Learning and Pattern RecognitionThis 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: Bayesian classification, regression, regularization, sparse regression, support vector machines, kernels, neural networks and gradient descent.
- ECE 538: Special Topics in Information Sciences and Systems: Advanced Wireless SystemsThis course is a graduate level course, focusing on advanced topics in wireless systems. It covers millimeter-wave networking, reconfigurable radio environments, wireless sensing, visible light communication, terehertz wireless networks, 5G/6G, wireless security, wireless energy harvesting, and autonomous networked UAVs. The students develop knowledge and skills to understand and critically evaluate research advances in emerging topics related to wireless systems. This course is held in a debate format and students will be able to defend and critically analyze research, both in writing and verbally.
- ECE 538B: Special Topics in Information Sciences and Systems: Theory of Deep Weakly Supervised LearningGraduate level course focusing on theoretical foundations of deep learning with a focus on weakly supervised aspects. The class covers the theoretical analysis tools used in deep learning including stochastic gradient, uniform convergence theory and statistical learning. The course focuses primarily on unsupervised learning and weakly supervised learning. Topics include generative models, self-training, transfer learning, representation learning, semi-supervised learning and other forms of self-supervised learning. Prior knowledge on statistics, linear algebra, probability theory and optimization is required.
- ECE 539/COS 512: Special Topics in Data and Information Science: Safety-Critical Robotic SystemsThe 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 545: Electronic DevicesIntroduction to principles of electron behavior in semiconductors and applications to device physics. Band diagrams, Metal-semiconductor contacts, Schottky barriers, p-n junctions. MOS electronics, FET's, bipolar transistors, solar cells, optical detectors, LED's.
- ECE 547: Selected Topics in Solid-State Electronics: Quantum Material SpectroscopyOne 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 550: Laser Spectroscopy: New Technologies and ApplicationsThe 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 554/MSE 553: Nonlinear OpticsA 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 CommunicationsThis 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 562: Design of Very Large-Scale Integrated (VLSI) SystemsAnalysis 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 568: Implementations of Quantum InformationThis 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 574: Security and Privacy in Computing and CommunicationsAs 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 581/ENE 581: Principles of Power ElectronicsThis 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 597: Electrical Engineering Graduate Project CourseGraduate Project Course. Under the direction of a faculty member the student carries out a graduate-level project and presents their results.
- EGR 491/ECE 491/ENT 491: High-Tech EntrepreneurshipThis hands-on course introduces students to analysis and actions required to launch and commercialize a tech company, through the use of Harvard Business School cases, visits from entrepreneurs, and two "field assignments". You will learn conceptual frameworks and analytical techniques for evaluating technologies, markets, and commercialization strategies. Additionally, you will learn how to attract and motivate the resources needed to start a company (e.g. people, corporate partners and venture capital), prepare business plans, structure relationships, refine product-market fit, and create and grow enterprise value.
- MAE 345/COS 346/ECE 345: Introduction to RoboticsRobotics 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.