Teaching

I love to teach. At Berkeley, I was a teaching assistant for 5 semesters.
CS170: Efficient Algorithms and Intractable Problems (Spring 2018)
CS189: Machine Learning (Spring 2017, Fall 2017)
CS70: Discrete Mathematics and Probability (Spring 2016, Fall 2016)

I was also a mentor for Computer Science Mentors. Some resources I’ve written:

• Markov Chains
• Bayesian approach to decision boundaries, discussion 3
• Regression, vectorizing objectives, and gradients, discussion 5
• Solution to Spring 2016 Midterm Isocontour Question
• Solution to Spring 2016 Final k-d tree problem

Here are some notes I’ve written / plan to write at some point on reinforcement learning:

• Intro to Reinforcement Learning
• Imitation Learning
• Model-free Reinforcement Learning
• Model-based Reinforcement Learning
• A guide to guided policy search

I received the Berkeley Oustanding GSI award in Spring 2017.