Teaching

I am teaching various courses including signal processing and power system topics at Lehigh University. Please sign up for courses on the University website. If you have any specific questions about course topics, feel free to email me and I will respond as soon as possible.

ECE 420: Advanced Circuits and Systems

Semester: Spring

Offered: 2022, 2023, 2024, 2025

Review of the fundamentals of Circuits and Systems theory, including the time and frequency domain response of linear time-invariant circuits. Equation formulation for general lumped circuits, including node voltage and loop current analysis. Basic graph theoretic properties of circuits including Tellegen’s Theorem. Discussion of passivity and reciprocity including multiport network properties. State space formulation and solution of general circuits (and systems). Modern filter concepts, including synthesis techniques for active filters and externally linear filters, such as Log Domain filters. Techniques for the analysis of weakly nonlinear systems, as time permits. Must have graduate standing

ECE 125: Random Signals and Learning

Semester: Fall

Offered: 2023, 2024

Introduction to random signals and analysis of linear time invariant (LTI) system response to random inputs. Modeling LTI systems using state space approach. Introduction to inference and learning, including basics of signal detection and estimation, linear regression, and linear time series models.

ECE 450: Machine Learning for Smart Grid Dynamic and Control

Semester: Fall

Offered: 2023, 2024

Introduction to microgrids, energy management in microgrids, economic dispatch and optimal power flow of microgrids, introduction to deep learning, deep learning-based ecnomic dispatch in microgrids, space vectors and dq frame, control of grid-following inverters, control of grid-forming inverters.

ECE 108: Signals and Systems

Semester: Fall

Offered: 2021, 2022

Continuous and discrete signal and system descriptions using signal space and transform representations. Includes Fourier series, continuous and discrete Fourier transforms, Laplace transforms, and z-transforms. Introduction to sampling.