Brian Yang

I am a Robotics PhD student at Carnegie Mellon University advised by Katerina Fragkiadaki and Jeff Schneider. Previously, I worked at Meta AI and completed my undergrad at UC Berkeley where I was fortunate to work with Dinesh Jayaraman, Roberto Calandra, Sergey Levine, and Kris Pister.

My research focuses on developing learning-based control algorithms at the intersection of generative modeling, model-based planning, and reinforcement learning. In my PhD, I have primarily focused on applying these ideas to autonomous driving. During my undergrad, I worked on a variety of real-world robot learning problems ranging from low-cost manipulation to microrobot locomotion.

Email / CV / GitHub / LinkedIn

Research

	Learning Driving Policies with Offline Counterfactual Reactive Simulation Adam Villaflor, Brian Yang, Katerina Fragkiadaki, John Dolan, Jeff Schneider In submission
	Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Following Brian Yang, Huangyuan Su, Nikolaos Gkanatsios, Tsung-Wei Ke, Ayush Jain, Jeff Schneider, Katerina Fragkiadaki CVPR 2024 arXiv / pdf / website
	Tractable Joint Prediction and Planning Over Discrete Behavior Modes for Urban Driving Adam Villaflor, Brian Yang, Huangyuan Su, Katerina Fragkiadaki, John Dolan, Jeff Schneider ICRA 2024 arXiv / pdf / code
	Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation Charles Sun, Jędrzej Orbik, Coline Devin, Brian Yang, Abhishek Gupta, Glen Berseth, Sergey Levine CoRL 2022 arXiv / pdf / blog / code
	MAVRIC: Morphology-Agnostic Visual Robotic Control Brian Yang, Dinesh Jayaraman, Glen Berseth, Alexei Efros, Sergey Levine RA-L + ICRA 2020 arXiv / pdf / project page
	DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation Mike Lambeta, Po-Wei Chou, Stephen Tian, Brian Yang, Benjamin Maloon, Victoria Rose Most, Dave Stroud, Raymond Santos, Ahmad Byagowi, Gregg Kammerer, Dinesh Jayaraman, Roberto Calandra RA-L + ICRA 2020 arXiv / pdf / project page
	REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning Brian Yang, Dinesh Jayaraman, Sergey Levine ICRA 2019 arXiv / pdf / project page / code
	Data-efficient Learning of Morphology and Controller for a Microrobot Thomas Liao, Grant Wang, Brian Yang, Rene Lee, Kris Pister, Sergey Levine, Roberto Calandra ICRA 2019 arxiv / pdf / project page / code
	Learning Flexible and Reusable Locomotion Primitives for a Microrobot Brian Yang, Grant Wang, Roberto Calandra, Daniel Contreras, Sergey Levine, Kris Pister RA-L + ICRA 2018 arXiv / pdf / project page / code

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