I'm a third-year student at UC Berkeley, studying Computer Science and Statistics.

I work with Sergey Levine in deep reinforcement learning, as well as Ben Brown in interpretable machine learning.

This spring, I'm teaching Stat 140: Probability for Data Science , a course I co-developed last year. I've taught Stat 134 previously as well.

A note on my name

Professional Summary


Quick ML

Simple code and explanations for the building block algorithms in ML

TensorFlow: A Beginner's Guide

A simple guide from linear regression to convolutional neural networks in Tensorflow

Featured Projects


Bearχive is an automated scraped collection of tests and study guides for UC Berkeley STEM courses, pulling from HKN, TBP, and internal Math databases.


An experiment in large scale Student Performance Analytics: AnnPod is designed to help instructors identify critical topics by analyzing Piazza contributions and topics through time

To see more of my projects, visit the projects page or my Github.