Brennan Shacklett (original) (raw)

I am a Ph.D candidate at Stanford University advised by Kayvon Fatahalian. My work revolves around designing graphics systems from the ground up for the new domain of training AI-based agents. Learning complex tasks requires agents to perform millions of simulated actions in virtual environments, presenting a challenging graphics workload with significant impact to research iteration times and accessibility. My current research focuses on evolving game engine and renderer architecture to enable high-throughput, GPU-accelerated simulation of thousands of learning environments simultaneously across a wide range of tasks. In the past, I've also worked on real-time image reconstruction techniques and debugging tools for hardware design. Prior to beginning my Ph.D., I received my B.S. and M.S. in Systems, also from Stanford University.

Publications

Habitat Synthetic Scenes Dataset (HSSD): An Analysis of 3D Scene Scale and Realism Tradeoffs for ObjectGoal Navigation Mukul Khanna, Yongsen Mao, Hanxiao Jiang, Sanjay Haresh, Brennan Shacklett, Dhruv Batra, Alexander Clegg, Eric Undersander, Angel Chang, Manolis Savva

IEEE / CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

Project Page | Paper | Dataset | Code

An Extensible, Data-Oriented Architecture for High-Performance, Many-World Simulation Brennan Shacklett, Luc Guy Rosenzweig, Zhiqiang Xie, Bidipta Sarkar, Andrew Szot, Erik Wijmans, Vladlen Koltun, Dhruv Batra, Kayvon Fatahalian

Transactions on Graphics 2023 (Presented at SIGGRAPH 2023)

Project Page | Paper | 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

Paper | Source code

Projects

Teaching & Industry Experience

6/23 - 12/24

Research Associate at Treyarch / Activision Central Technology

Exploring game development applications of rapid agent training.

6/21 - 9/21

Research Intern in the Intelligent Systems Lab at Intel

Working on 3D simulation and rendering for reinforcement learning and robotics under Vladlen Koltun.

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.

6/19 - 9/19

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.