ECE 4271 VLSI Design

ECE 4271 VLSI Design introduces the foundations of Integrated Circuits (ICs) and Very Large-Scale Integration (VLSI) technology. In modern computing systems, information is primarily processed in the format of digital signals. Therefore, this course focuses on integrated digital logic design, covering essential concepts and techniques related to VLSI circuit design, such as timing, power, interconnect, etc. Through the labs, students are expected to master commercial electronic design tools such as SPICE and Cadence Virtuoso by designing electronic modules.

ECE 4235 Sensing and Processing in Robotic Applications

This class focuses on the "sensing" aspect of robotics, particularly in computer vision processing and other sensing techniques using deep learning methods. The learning objectives include the ability to conduct top-level analysis for a computer vision system and to write, test, and evaluate computer vision algorithms for pattern recognition in the context of robotics using deep learning.

Upon completion of the course, students will grasp the fundamentals of robotic sensing and the significance of sensing in robotics. They will acquire knowledge in processing visual signals captured by cameras through Artificial Neural Networks, gain expertise in processing range sensing (including Lidar for robotic perception), and understand inertial sensing, GPS, and odometry in the realm of robotics.

ECE 5435 High-Speed Circuit Design

ECE 5435 High-Speed Circuit Design introduces the foundations and techniques for dealing with high frequency (~GHz) signals using transmission line theory, signal integrity analysis, and power delivery networks. In addition, the course covers simulation techniques, including the commercial full-wave simulator Ansys HFSS (high-frequency structure simulator). The course also provides an introduction to measurement skills using industry-standard instruments such as Vector Network Analyzers (VNA) and Time Domain Reflectometers (TDRs). This course equips engineers with practical skills and fundamental theory to minimize issues such as crosstalk and signal reflections in high-speed circuit designs.

ECE 5900 Neuromorphic Robotic System

ECE 5900 Neuromorphic Systems for Robots offers an interdisciplinary perspective on Neuromorphic Computing and Brain-Inspired Computing. The course covers neuroscience, algorithms, hardware implementations, and applications. In this course, students will learn how to build computational models of brains and use neuromorphic systems to control robots. The topics covered include building computational models of neurons and synapses, designing electronic neurons and synapses with CMOS technology, training Spiking Neural Networks, and controlling autonomous robots with neuromorphic systems.