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