The course deals with the modeling and simulation of physical systems. It introduces the fundamental techniques to generate and solve the equations of a static or dynamic system. Special attention is devoted to complexity issues and to model order reduction methods, presented as a systematic way to simulate highly-complex systems with acceptable computational cost. Examples from multiple disciplines are considered, including electrical/electromagnetic engineering, structural mechanics, fluid-dynamics. Students are encouraged to work on a project related to their own research interests.

Special topics offered by graduate units in area of Electromagnetics. Content of courses may change each time they are offered and are developed to cover emergeing issues or specialized content.

This course outlines the principles of designing modern microwave and RF circuits. Signal-integrity issues in high-speed digital circuits are also examined. The wave equation, ideal transmission lines. Transients on transmission-lines. Planar transmission lines and introduction to MMICs. Designing with scattering parameters. Planar power dividers, directional couplers. Microwave filters. Solid-state microwave amplifiers, noise, diode-mixers, RF receiver chains, oscillators.

Computational electromagnetism plays a crucial role in many areas of scientific research and industrial applications, including antennas, radar, metamaterials, integrated circuit design, quantum computing, energy generation and transmission, optics, medical imaging, sensing, radioastronomy. This course focuses on integral equation methods for solving Maxwell's equations, covering theory, implementation, applications and recent research developments. Electrostatic problems are first used to introduce students to fundamental concepts: integral formulations of Maxwell's equations, the Green's function, discretization and testing aspects, computation of singular integrals. After a review of direct and iterative methods to solve linear systems, we discuss the most prominent techniques for accelerating integral equation methods, including fast multipole algorithms, FFT-based approaches, and hierarchical matrices. The general case of electrodynamics is considered next, including the choice of basis functions, modeling of excitations, postprocessing of results, modeling penetrable objects. Finally, selected topics from recent research will be presented.

Throughout the course, examples drawn from real applications will be presented, related to integrated circuit design, antenna modeling, and metamaterials. The course engages students in lectures with an active, hands-on approach based on learning notebooks that both exemplify the concepts covered in lectures, as well as require students to immediately put them into practice. Students will be required to solve 3 to 4 assignments and work on a final project, typically related to their research interests. The project deliverables will be: an IEEE-formatted report, a presentation, and the submission of the developed codes.

A design intensive overview of high-speed, RF, mm-wave monolithic, and silicon photonics integrated circuits for wireless, automotive radar sensors, and optical fiber systems with an emphasis on specific high-frequency circuit analysis and design methodologies, device-circuit topology interaction and optimization. Small-signal, noise, large-signal, high-frequency common-mode and differential-mode matching and stability, digital control of tuned circuits, methodologies for maximizing circuit bandwidth, high speed CML gate design, as well as layout and isolation techniques will be discussed. Students will participate in six take-home assignments on the analysis, modelling, schematic and layout design of mm-wave transistors, inductors, and circuits using advanced RF CMOS and SiGe BiCMOS technologies.

An advanced digital hardware course dealing with the design of large digital systems implemented using FPGA and ASIC technologies. Topics include architecture design, design flows, HDL design, clocking, and interfacing.

The approaches and algorithms for automatic synthesis, with a concentration on the back-end of the CAD flow. Topics covered will include: technology mapping, partitioning, placement, routing, timing analysis, and physical synthesis. The course will include experience with existing CAD tools and building new tools, and will pay special attention to synthesis issues as applied to Field-Programmable Gate Arrays.

The course introduces a design methodology for very-large-scale-integration (VLSI) circuits using advanced computer-aided-design (CAD) tools. The focus is on learning Cadence integrated circuit (IC) design tools to implement the IC design flow. The methodology includes the steps of: custom digital circuit design, automated digital circuit synthesis, digital and mixed-signal circuit simulation, custom layout design, and automated layout generation. The course includes several projects using a 65nm CMOS process: 1) transistor characterization, 2) full custom digital circuit and layout design, 3) automated digital circuit synthesis and layout place-and-route, and 4) team-based design of a full IC employing the methodology learned in the course.

This course deals with integrated circuit implementations of digital communication. Topics include circuits for channel equalization (both at the transmitter and the receiver), clock and data recovery, coding, and modulation schemes. Practical examples will be derived from wireline communication including chip-to-chip and backplane signaling.

This course presents the electrical characteristics, thermal characteristics, packaging techniques and applications of state-of-the-art power semiconductor devices. In particular, the device structure and fabrication technology for power MOSFETs and IGBTs will be discussed extensively. The integration of these power devices to form Smart Power IC and HV CMOS technologies will also be introduced. An industrial standard Technology CAD tools from Crosslight Inc. will be used extensively to demonstrate the design, analysis, modelling, and optimization of these power devices. Design projects targeting methods to achieve high breakdown voltage, low on-resistance, fast switching speed, and high reliability/ruggedness will be carried out. In addition, the students will be also exposed to selection considerations for "off-the-shelf" devices that would meet the circuit or system level specifications.

An overview of continuous-time and discrete-time signal processing techniques, and the analysis and design of the analog and mixed-signal circuit building blocks which are used to implement them in modern electronic systems. Topics covered are: i) analysis, specification, simulation, and design of continuous-time filters with linear transconductors and op-amps, ii) phase-domain model, noise model, and design methodology for low phase noise Phase Lock Loops and associated building blocks (VCO, phase-frequency detector, charge pump), iii) Discrete-time signal analysis using z-transform, iv) discrete-time filter design based on switched capacitors, and v) fundamentals, specification, architectures, building blocks (comparator, THA), and characterization techniques for digital-to-analog and analog-to-digital converters. Cadence Analog Artist is used for lab assignments.

The course deals with the technology and design of analog, digital and RF integrated circuits, including exposure to computer aided IC design tools at the semiconductor process, device, and circuit layout level. Topics include: IC fabrication review, MOS IC Process Modules and Components; RF (Bi) CMOS IC Process Modules and Components; Compact Modelling, Characterization, and Design Automation; Bipolar/CMOS Digital, Analog, and RF IC Building Blocks; Packaging and Yield. The labs will expose students to the major steps in the development of a multi-purpose (Bi) CMOS process.

This course develops the theoretical background of quantum electronics and electro-optics and their applications to laser theory. The course is intended for engineering students with limited working knowledge of quantum mechanics. Topics include Schroedinger wave equation, quantum wells, hydrogen and multi-electron atoms, angular momentum and electron spin, harmonic oscillators and molecular structure, energy bands of solids, electric dipole moments, perturbation theory, and interaction of light with matter.

This course develops an in-depth understanding of ultrafast optical fundamentals and device technology. Topics to be covered include: short optical pulse generation; nonlinear optical effects; ultrafast optical phenomena; short optical pulse characterization techniques; pulse compression and temporal shaping; temporal and spatial solitons; and, as time permits, photonic devices and applications. The remainder of the course will be devoted to student presentations of papers on these topics in the current research literature. Students are expected to do substantialreading and study of the material in advance of the class lectures so that class discussions can focus on questions and issues raised by the students.

Special topics offered by graduate units in area of Photonics. Content of courses may change each time they are offered and are developed to cover emerging issues or specialized content.

This course provides the fundamentals of laser processing and advanced topics in application areas pertinent to photonics, electronics, medical, automotive, aerospace, and general manufacturing industries. Topics include cw to ultrafast laser systems, common approaches to beam delivery systems, and fundamentals of laser interactions with insulators, conductors, dielectrics, plasma, and soft tissues. Photothermal and photochemical processes and heat-flow models are discussed in the context of traditional applications such as welding, cutting, marking, etching and rapid-prototyping. Advanced and emerging application areas are photolithography, corneal sculpturing, refractive-index control in glasses, micromachining, semiconductor annealing, circuit-board processing, laser-induced breakdown spectroscopy, photonic-components, and surface texturing.

The aim of this course is to equip graduate students with the skills necessary to carry out practical design exercises and produce integrated optical components. The course will introduce the numerical tools used to simulate waveguides, the material systems and parameters in common use and typical device configurations. Students will develop a practical understanding of basic integrated components, including: Y-junctions, directional couplers, interferometers, and multi-mode interferometers (MMIs). The course will also consider typical approaches towards monolithic and hybrid integration.

This course focuses on photonic components which generate or absorb light. Lasers: spontaneous and stimulated emission, gain and absorption, gain broadening, modulation dynamics, mode-locking, Q-switching; semiconductor lasers. Photodetectors: absorption, photo-generated currents, noise in detection.

This course provides an introduction to error control techniques, with emphasis on decoding algorithms. Topics include algebraic coding theory: finite fields, linear codes, cyclic codes, BCH codes and decoding, Reed-Solomon codes; iterative decoding: codes defined on graphs, the sum-product algorithm, low-density parity-check codes, turbo codes.

This course deals with fundamental limits on communication, including the following topics: entropy, relative entropy, and mutual information: entropy rates for stochastic processes; differential entropy; data compression; the Kraft inequality; Shannon-Fano codes; Huffman codes; arithmetic coding; channel capacity; discrete channels; the random coding bound and its converse; the capacity of Gaussian channels; the sphere-packing bound; coloured Gaussian noise and water-filling; rate-distortion theory; the rate-distortion function; multiuser information theory.

This course provides an introduction to error-correction, signal processing, and inference on "graphs." We will start with graph-based error correcting codes and associated decoding methods and continue on to topics such as signal processing on graphs and compressive sensing. Viewing (and designing) error-correction codes and decoding algorithms from a graph-based viewpoint revolutionized the theory and practice of error correction starting in the 1990s. While the initial focus of the course is on error correction, the techniques used to analyze the performance of these codes, and the algorithmic methods used to decode them, connect to diverse areas of statistical inference including machine learning and statistical physics. Topics concerning error-correction coding in past offerings of the course have included turbo, low-density parity-check (LDPC), "fountain," spatially coupled, and Polar codes; iterative decoding techniques such as the sum-product algorithm; code design techniques; and threshold analysis via density evolution. Topics concerning other applications of signal processing and inference on graphs have included signal processing on graphs ("graph-SP"), compressed sensing, and connections between graphical inference and convex optimization.

The error-correction portion of the course is designed to complement ECE1501H, but that course is not a prerequisite. Students in engineering, the computer sciences, and math will find this course interesting.

This course is designed for students with a background in communication systems and information theory, interested in doing research in machine learning. The first half of the course will focus on one-shot approaches in multiuser information theory and discuss some applications to machine learning. The second half will develop information theoretic bounds on the generalization error in statistical learning. The final course project is expected to be on a topic at the intersection of information theory and machine learning.

This course provides a comprehensive coverage of the theoretical foundation and numerical algorithms for convex optimization with engineering applications. Topics include: convex sets and convex functions; convex optimization problems; least-square problems; optimal control problems; Lagrangian duality theory. Karush-Kuhn-Tucker (KKT) theorem; Slater’s condition; generalized inequalities; minimiax optimization and saddle point; introduction to linear programming, quadratic programming, semidefinite programming and geometric programming; numerical algorithms: descent methods, Newton’s method, interior-point method; convex relaxation; applications to communications and signal processing.