Coursework

Computer Science

Electrical and Computer Engineering

Miscellaneous


Teaching

CS 4782: Deep Learning
Spring 2025
This class is an introductory course to deep learning. It covers the fundamental principles behind training and inference of deep networks, the specific architecture design choices applicable for different data modalities, discriminative and generative settings, and the ethical and societal implications of such models.
CS 4780: Machine Learning
Fall 2023, Spring 2024, Fall 2024
The course provides an introduction to machine learning, focusing on supervised learning and its theoretical foundations. Topics include regularized linear models, boosting, kernels, deep networks, generative models, online learning, and ethical questions arising in ML applications.
ECE 4960: Dynamic Networks and Games
Spring 2024
This course will provide the necessary mathematical and modeling tools needed to describe and understand these network systems. Questions of interest will be how the network structure impacts the dynamics of network systems, how network properties can be exploited to maximize system performance or resilience and how one can address these questions while also accounting for strategic human behavior. The course will introduce tools that can be used to address these questions and successfully overcome challenges related to the coupled, distributed, and large-scale nature of network systems in environments with limited sensing, communication, and control capabilities.
ECE 6210: Theory of Linear Systems
Fall 2024
State-space and multi-input-multi-output linear systems in discrete and continuous time. The state transition matrix, the matrix exponential, and the Cayley-Hamilton theorem. Controllability, observability, stability, realization theory. At the level of Linear Systems by Kailath.