Adithyavairavan Murali
University of California, Berkeley, Carnegie Mellon University, Nvidia (United Kingdom)
Papers
17
Total Citations
677
H-Index
12
About
Adithyavairavan Murali is a robotics researcher whose work spans surgical robotics, robot learning, and human-robot interaction. He has made substantial contributions to automating complex surgical subtasks, including pioneering learning-by-observation techniques that enable robotic systems to perform multilateral cutting on deformable tissue phantoms using the da Vinci Research Kit — a paper that has garnered over 180 citations. His early work on Gaussian Process Regression for cable-driven surgical robots (76 citations) and haptic palpation probes for minimally invasive surgery (70 citations) demonstrated his ability to bridge hardware design with intelligent control. Murali's research evolved toward broader challenges in robot learning, including reducing dataset bias in home environments (61 citations) and enabling multi-robot transfer learning through hardware-conditioned policies. His open-source contribution, PyRobot (51 citations), has lowered barriers to robotics research by providing a unified, hardware-agnostic framework built atop ROS. More recently, he has advanced task-oriented grasping and human-to-robot handover benchmarking through simulation environments like HandoverSim. Across these domains, Murali's collective body of work reflects a consistent drive to make robotic systems more adaptable, generalizable, and deployable in real-world settings.
Research Focus
Key Achievements
Top Papers
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- 5Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias61 citations · 2018
- 6PyRobot: An Open-source Robotics Framework for Research and Benchmarking51 citations · 2019
- 7Hardware Conditioned Policies for Multi-Robot Transfer Learning33 citations · 2018
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