Phased arrays are a key component in radars, wireless and satellite communications, remote sensing and imaging systems, and in scientific instruments such as radio telescopes. This course will provide a working knowledge of the key parameters of modern phased array antenna systems. Students will learn to critically evaluate the performance of phased array antenna systems and their main building blocks, with emphasis on factors that are important for high-performance radar and communication systems. Concepts, theory models and design principles will be developed.

Lecture, laboratory. Metrology fundamentals. Advanced microwave measurement techniques including error correction, de-embedding, and noise effects in amplifiers and oscillators. Prerequisites: familiarity with microwave CAD software, basic microwave theory.

Lecture, laboratory. Metrology fundamentals. Advanced microwave measurement techniques including error correction, de-embedding, and noise effects in amplifiers and oscillators. Prerequisites: familiarity with microwave CAD software, basic microwave theory.

Theory and techniques used in the design of modern microwave and millimeter wave active circuits. Emphasis on amplifier and oscillator circuits using devices such as FETs, HEMTs, HBTs and optoelectronic devices. Modern reference material used as much as possible.

Theory and techniques used in the design of modern microwave and millimeter wave active circuits. Emphasis on amplifier and oscillator circuits using devices such as FETs, HEMTs, HBTs and optoelectronic devices. Modern reference material used as much as possible.

This course will introduce students to the area of green computing. The course will cover emerging problems associated with the rapid growth of energy consumption in modern computing infrastructures, i.e. data centers, and discuss new research focused on mitigating these problems. The course will also cover ways to leverage computation, networking, and sensing to improve the energy-efficiency of the electric grid, e.g. by automatically regulating energy consumption in buildings, homes, etc.

Fundamental concepts and systems aspects of computer networks. Topics include a review of the layered Internet architecture and encompass router design, lookup and classification algorithms, scheduling algorithms, congestion control, wireless protocols, and network security. The goal of the course is to explore the key technical and research questions in computer networks as well as to convey the necessary analytical, simulation, and measurement techniques.

A graduate version of E&C-Eng 570 which includes additional readings from research papers and coverage on concepts for specific operating system modalities, such as distributed, embedded, mobile, and secure operating systems.

A graduate course in computer algorithms. Includes algorithms for sorting, optimization, scheduling, and data management; graph algorithms; random algorithms; NP-completeness. Prerequisites include close familiarity with data structures, probability theory, and linear algebra.

This course studies architectural techniques for efficient hardware design for machine learning (ML) systems including training and inference. Course has three parts. First part deals with convolutional and deep neural network models. Second part deals with parallelization techniques for improving performance of ML algorithms.