Analysis and synthesis of antenna elements and arrays. Topics include linear antennas, self and mutual impedances, aperture, travelling wave, and broadband antennas. Prerequisite: E&C-Eng 334 or equivalent.

This course covers various topics Scientific Computing including: basic numerical techniques of linear algebra and their applications, data formats and practices, matrix computations with an emphasis on solving sparse linear systems of equations and eigenvalue problems. Students will learn about the state-of-the-art programming practices in numerical linear algebra, and will be introduced to numerical parallel algorithms and parallel programming with OpenMP, MPI and hybrid.

Introduction to fundamental biological neuron models, algorithms and techniques for learning spatiotemporal patterns, and software frameworks for implementing spike-based computation. Understanding of the hardware foundation for bio-inspired computation from transistors and emerging devices to neuromorphic circuits and systems. Investigation of low-power, low-latency applications of neuromorphic engineering in machine vision, robotics, autonomous vehicles, etc.

This course is the first introductory course in the field of photonics and introduces students to the fundamental operating principles of optical components and photonic devices. Three different descriptions of optical propagation and interaction (geometrical optics, wave optics, and electromagnetic optics) with increasing complexity and accuracy are presented. Physical phenomena and photonic devices whose operation can be described within the scope of each theory are introduced and discussed.

A graduate version of E&C-Eng 568. Quantitative study of pipelined processor architectures, memory, Input/Output, RISC processors and vector machines. Prerequisite: undergraduate courses in digital design and hardware organization.

Modern techniques for synthesis and verification of digital systems. Topics in synthesis cover high-level synthesis, decision diagrams, combinational and sequential logic optimization. Topics in verification include symbolic techniques, equivalence checking, satisfiability, FSM traversal and state reachability analysis. Prerequisites: undergraduate courses in digital logic design and hardware organization.

The impact of VLSI technology on digital systems and architectures. A variety of applications of these architectures explored with emphasis on digital signal processing and other arithmetic-intensive computations. Prerequisites: E&C-ENG 558, 568.

A graduate version of E&C-Eng 558 which includes additional readings in VLSI architecture, CAD, and systems. A more ambitious design project required, which can be related to the student's research or possibly another advanced E&C-Eng course such as digital signal processing, control, computer architecture, or computer graphics. Prerequisites: E&C-ENG 212 and 221 or equivalent.

Machine learning is employed in an increasingly wide range of applications. This course will cover two sides about machine learning. On one side, we will talk about recent systems research in machine learning, such as efficient training and inference, distributed and parallel learning systems, and debugging and profiling of ML applications. On the other side, we will discuss research in using machine learning for systems, e.g., identifying performance, reliability, and scalability issues.

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