Brennan Shacklett

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.

Publications

Large Batch Simulation for Deep Reinforcement Learning

Brennan Shacklett, Erik Wijmans, Aleksei Petrenko, Manolis Savva, Dhruv Batra, Vladlen Koltun, Kayvon Fatahalian

International Conference on Learning Representations (ICLR), 2021

Project Page | Training & Simulator Source code | Renderer Source Code

Encoding, Fast and Slow: Low-Latency Video Processing Using Thousands of Tiny Threads

Sadjad Fouladi, Riad Wahby, Brennan Shacklett, K Balasubramaniam, W Zeng, R Bhalerao, A Sivaraman, G Porter, and Keith Winstein

USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2017

Source code

Projects

Continuous Learning for Interactive Denoising of Path Traced Content

Masters Thesis, advised by Anjul Patney, Marco Salvi, Aaron Lefohn, and Kayvon Fatahalian

Source code

Interactive Circuit Debugging and Simulation with Just In Time Compilation

Undergraduate Honors Thesis, advised by Pat Hanrahan

Source code

Teaching & Industry Experience

4/19 - 6/19, 4/20 - 6/20

Head Course Assistant for CS348B: Image Synthesis Techniques

Developed new assignments and assisted students. Class taught by Pat Hanrahan and Matt Pharr.

6/20 - 9/20

Research Intern in the Real-Time Rendering group at NVIDIA Research

Worked with Marco Salvi on image supersampling techniques (DLSS) under Aaron Lefohn.

6/16 - 9/16

Research Intern in the Video Compression group at Mozilla Research

Improved performance of the AV1 rate-distortion optimizer under Tim Terriberry.