EGRE254 - Digital Logic Design

An introduction to digital logic design with an emphasis on practical design techniques and circuit implementations. Topics include number representation in digital computers, Boolean algebra, theory of logic functions, mapping techniques and function minimization, design of combinational, clocked sequential and interactive digital circuits such as comparators, counters, pattern detectors, adders and subtractors. Asynchronous sequential circuit concepts are introduced. Students will use the above basic skills in the laboratory to design and fabricate digital logic circuits. For this course I developed an full series of introductory videos.

Semesters taught: Spring-Fall 2021, Spring-Fall 2022

EGRE491 - Modeling and Control of Cyber-physical Systems

This course builds students’ experience with modeling, simulating, and controlling cyber-physical systems (CPS). Students will learn the fundamentals of modeling linear and nonlinear dynamical systems, including the numerical methods necessary to simulate and evaluate them. Additionally, students will develop their skills modeling discrete dynamics, such as state machines, within the context of control. State-space control theory techniques, such as state and output feedback, as well as advanced topics in nonlinear control will be used to build controllers for modern CPS. Additional topics in estimation and control over networks will be explored. The course’s lab will allow students to make course concepts concrete by applying mathematical, programming, and systems engineering skills.

Semester taught: Spring 2023

EGRE691 - Autonomous Cyber-physical Systems

In the near future, autonomous cyber-physical systems will be deployed into many facets of the global economy: from transportation to advanced manufacturing. This course introduces the architectures and algorithms that enable the development and deployment of mobile, autonomous cyber-physical systems. Students will develop systems that perceive and take action in the physical world using control-theoretic and machine learning techniques. This course reinforces theory with practical assignments that leverage software tools common in the autonomous system community.

Semesters taught: Fall 2020-2021

Capstone Design

I developed and managed six different Capstone Design teams from 2020-2023. These projects ranged from autonomous river sensors to fruit picking robot manipulators.

Back to teaching…