Teaching

During my career I developed an active-learning teaching style that engages students with the course material through online lectures and interactive class sessions. The courses I have taught are listed below, as well as the institution where I delivered them.

Introduction to Machine Learning

This two day lab course teaches technical professionals core theoretical concepts and algorithms in machine learning. The active lectures blend short exercises with applied lab work. Some subjects covered include clustering, linear regression, decision trees, and deep neural networks. Students learn how to apply popular Python machine learning libraries, such as sklearn and keras.

Machine Learning: Beyond the Buzz

This one day course introduces the audience to the broad field of machine learning. It explains to students the requirements, advantages, and  disadvantages of machine learning enabled capabilities. Students will be able to see beyond the buzz and focus on the useful tools that machine learning can provide.

Applied Control

This course introduced students to the fundamental principles and applications of applied control. Topics include analytical techniques for digital control, design using transform and state space methods, and multi-input, multi-output systems. The laboratory is dedicated to hardware implementation of proportional, integral, derivative (PID) control and other advanced controllers, as well as computational methods for discrete system analysis and controller design. This course also presented advanced topics from distributed control systems. Students developed and deployed their synthesized controllers on National Instruments Compact RIO platforms.

Engineering Physics: E&M

This course introduced the student to the topics of static electricity, electric fields, Gauss’ Law, electric potential, capacitance, resistance, current, voltage, simple electric circuits, magnetic fields, Ampere’s Law, Faraday’s Law, and inductance. This course pioneered a flipped classroom structure at York College, using online lectures that introduced students to the core concepts that would be fleshed out in the classroom discussion and exercises.

Fundamentals of Electrical Engineering

This course covered topics in AC and DC linear circuit analysis including Kirchhoffs Laws, voltage and current division, nodal and mesh analyses, superposition, equivalent circuits and power, and the role of circuit components. Steady-state AC circuit topics such as phasors, impedance, frequency response, filtering, damping, resonance, and power were also covered. This course used the active learning and flipped classroom structure I developed in my Engineering Physics E&M course.

Senior Capstone

This capstone design course required the careful instruction and management of a team of senior ECE students in a team project. For three of the four year I instructed, we attended the Intelligent Ground Vehicle Competition (IGVC). Another year, the students developed a prototype bike sharing system for the campus and surrounding community.

Game Theory

This course developed economic game theory through theoretical and programming exercises. Furthermore, students learned about more recent applications of game theory to multi-agent systems. I served as a lecturer and grader for this course.