Sample Technical Courses

I proposed, designed and taught CS81SI AI Interpretability & Fairness at Stanford listed under CS81SI archived here in Spring 2020, with the invaluable support of my faculty sponsors Professor James Zou and Professor Omer Reingold. For background on the class and similar class offerings, please check out this School of Engineering post. For more information on the course, please feel free to reach out to me.

Relevant CS / Math Courses

I pursued a B.S in Math and M.S in CS. If you are a current Stanford student deciding on courses and majors, I wrote up some thoughts that were helpful in guiding my selection.

CS 107, 109, 110, 161 - All of CS Core

CS 140 - Operating Systems

CS 144 - Computer Networking - Best TCP Sender Assignment Award

CS 205L - Continuous Methods in Machine Learning

CS 229 - Machine Learning, Project on Financial Ratio Predictor Efficacy On Long-Term Investment Outcome

CS 224N - Natural Language Processing with Deep Learning, Project on Character-Aware Direct Output Language Models

CS 231N - Convolutional Neural Networks for Visual Recognition, Project on Non-Linear Concept Vectors

CS 234 - Reinforcement Learning, Project on Intrinsic Motivation in Meta Learning

CS 236 - Deep Generative Models, Project on Entropy Regularization in Conditional GANs

CS 255 - Cryptography

MATH 63DM - Modern Mathematics: Discrete Methods

MATH 104 - Applied Matrix Theory

MATH 120 - Groups & Rings (Honours, Writing in the Major)

MATH 121 - Galois Theory

MATH 148 - Algebraic Topology

MATH 158 - Stochastic Processes

MATH 159 - Discrete Probabilistic Methods

MATH 171 - Real Analysis (Honours, Writing in the Major)

MATH 231 - Mathematics and Statistics of Gambling

MATH 233B - Topics in Combinatorics