Sid Reddy

Google Scholar | Github | Twitter | Resume
sgr [at] berkeley [dot] edu
I'm a fourth-year computer science Ph.D. student at the Berkeley Artificial Intelligence Research Lab, where I have the privilege of being co-advised by Sergey Levine and Anca Dragan. I work on machine learning algorithms for augmenting human control in domains like robotics and education. My research statement contains details.

Publications


Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine, X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback, International Conference on Learning Representations (ICLR), 2021.
[PDF] [OpenReview]
Siddharth Reddy, Sergey Levine, Anca D. Dragan, Assisted Perception: Optimizing Observations to Communicate State, Conference on Robot Learning (CoRL), 2020.
[PDF] [arXiv] [Videos] [Code]
Siddharth Reddy, Anca D. Dragan, Sergey Levine, Shane Legg, Jan Leike, Learning Human Objectives by Evaluating Hypothetical Behavior, International Conference on Machine Learning (ICML), 2020.
[PDF] [arXiv] [Blog] [Videos] [Code]

Siddharth Reddy, Anca D. Dragan, Sergey Levine, SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards, International Conference on Learning Representations (ICLR), 2020.
[PDF] [arXiv] [OpenReview] [Code]

Gokul Swamy, Siddharth Reddy, Sergey Levine, Anca D. Dragan, Scaled Autonomy: Enabling Human Operators to Control Robot Fleets, International Conference on Robotics and Automation (ICRA), 2020.
[PDF] [arXiv]

Siddharth Reddy, Anca D. Dragan, Sergey Levine, Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior, Neural Information Processing Systems (NeurIPS), 2018.
[PDF] [arXiv] [Videos] [Code]

Siddharth Reddy, Anca D. Dragan, Sergey Levine, Shared Autonomy via Deep Reinforcement Learning, Robotics: Science and Systems (RSS), 2018.
[PDF] [arXiv] [Blog] [Videos] [Code]

Siddharth Reddy, Igor Labutov, Siddhartha Banerjee, Thorsten Joachims, Unbounded Human Learning: Optimal Scheduling for Spaced Repetition, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016.
[PDF] [arXiv] [Code]