Teaching

Spring 2022

Advanced Topics in Neural Networks

An upper-graduate level course covering papers within the last five years. Topics included constructing Neural Networks, Gradient Descent convergence, Interpolation and Memorization, Neural Tangent Kernel, Curriculum Learning.

Fall 2021

Introduction to Operating Systems

An undergraduate level course covering the following topics: Processes and Threads, Scheduling, Concurrency, Deadlock, Virtual Memory, File System, Input/Output.

Spring 2021

Theory of Reinforcement Learning

A graduate level course covering the following topics: Markov Decision Processes, Value Iteration and Policy Iteration, UCB algorithms, Sample Complexity bounds.