I am a Ph.D. student at Stanford University advised by Kayvon Fatahalian. My broad interests include problems in the intersection between graphics, systems, and machine learning. Recently, my research has focused on high performance rendering in a variety of different regimes. Prior to beginning my Ph.D., I received my B.S. and M.S. in Systems, also from Stanford University.
Megaverse: Simulating Embodied Agents at One Million Experiences per Second
International Conference on Machine Learning (ICML), 2021
Large Batch Simulation for Deep Reinforcement Learning
International Conference on Learning Representations (ICLR), 2021
Encoding, Fast and Slow: Low-Latency Video Processing Using Thousands of Tiny Threads
USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2017
Teaching & Industry Experience
Research Intern in the Intelligent Systems Lab at Intel
Working on 3D simulation and rendering for reinforcement learning and robotics under Vladlen Koltun.
Head Course Assistant for CS348B: Image Synthesis Techniques
Developed new assignments and assisted students. Class taught by Pat Hanrahan and Matt Pharr.
Research Intern in the Real-Time Rendering group at NVIDIA Research
Worked with Marco Salvi on image supersampling techniques (DLSS) under Aaron Lefohn.
Research Intern in the Video Compression group at Mozilla Research
Improved performance of the AV1 rate-distortion optimizer under Tim Terriberry.