| 2025 | ICLR | Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning. | Patrick Yin, Tyler Westenbroek, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta |
| 2024 | CoRL | Learning to Walk from Three Minutes of Real-World Data with Semi-structured Dynamics Models. | Jacob Levy, Tyler Westenbroek, David Fridovich-Keil |
| 2023 | CoRL | Enabling Efficient, Reliable Real-World Reinforcement Learning with Approximate Physics-Based Models. | Tyler Westenbroek, Jacob Levy, David Fridovich-Keil |
| 2023 | ICML | The Power of Learned Locally Linear Models for Nonlinear Policy Optimization. | Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu |
| 2022 | CoRL | Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning. | Tyler Westenbroek, Fernando Castaeda, Ayush Agrawal, Shankar Sastry, Koushil Sreenath |
| 2020 | ICRA | Feedback Linearization for Uncertain Systems via Reinforcement Learning. | Tyler Westenbroek, David Fridovich-Keil, Eric Mazumdar, Shreyas Arora, Valmik Prabhu, S. Shankar Sastry, Claire J. Tomlin |