General Information
Details
My research focuses on identifying and studying structural priors that can serve as generalizable inductive biases for embodied intelligence. I direct the Structured Techniques for Algorithmic Robotics (STAR) Lab, where we develop computational and learning frameworks designed to improve robots’ efficiency, reliability, and self-sufficiency across diverse applications such as dexterous manipulation and multi-robot systems.
My teaching interests include fundamentals of robotics and artificial intelligence, and advanced topics in robot learning, robotic manipulation, and multi-agent systems. I enjoy teaching project-based courses with hands-on experience. I routinely teach:
- CS 3630: Introduction to Robotics and Perception
- CS 4803: Advanced Robotic Manipulation (ARM)
- CS 7631: Multi-Robot Systems
- Z. Yang, A.P. Hu, H. Ravichandar, “Towards Automated Chicken Deboning via Learning-based Dynamically-Adaptive 6-DoF Multi-Material Cutting”, IEEE International Conference on Robotics and Automation (ICRA), 2026.
- Y. Liu*, W.C. Shin*, Y. Han, Z. Chen, H. Ravichandar, D. Xu, “ImMimic: Cross-Domain Imitation from Human Videos via Mapping and Interpolation”, Conference on Robot Learning (CoRL), 2025. [Oral Spotlight - Top 3.6%]
- K. Fu*, S. Jain*, P. Howell, H. Ravichandar, “Capability-Aware Shared Hypernetworks for Flexible Heterogeneous Multi-Robot Coordination”, Conference on Robot Learning (CoRL), 2025.
- S. Kailas, S. Jain, H. Ravichandar, “Evaluating and Improving Graph-based Explanation Methods for Multi-Agent Coordination”, Autonomous Agents and Multi-Agent Systems (AAMAS), 2025
- Y. Han, Z. Chen, K. Williams, H. Ravichandar, “CIMER: Learning Prehensile Dexterity by Imitating and Emulating State-only Observations”, IEEE Robotics and Automation Letters (RA-L), 2024.
- J. Liu*, G. Neville*, S. Chernova, H. Ravichandar, “Q-ITAGS: Quality-Optimized Spatio-Temporal Heterogeneous Task Allocation with a Time Budget”, International Symposium of Robotics Research (ISRR), 2024.
- Y. Han, M. Xie, Y. Zhao, H. Ravichandar, “On the Utility of Koopman Operator Theory in Learning Dexterous Manipulation Skills”, Conference on Robot Learning (CoRL), 2023. [Oral Spotlight – Top 6.6%]
- R. Torbati, S. Lohiya*, S. Singh*, M. S. Nigam, H. Ravichandar, “MARBLER: An Open Platform for Standardized Evaluation of Multi-Robot Reinforcement Learning Algorithms”, International Symposium on Multi-Robot & Multi-Agent Systems (MRS), 2023. [Best Paper Award]
- A. Messing*, G. Neville*, S. Chernova, S. Hutchinson, H. Ravichandar, “GRSTAPS: Graphically Recursive Simultaneous Task Allocation, Planning, and Scheduling”, International Journal of Robotics Research (IJRR), vol. 41, no. 2, 2022.