Rishi Kapadia
Papers
3
Total Citations
156
H-Index
3
About
Rishi Kapadia is a robotics researcher whose work sits at the intersection of surgical robotics, haptic sensing, and human-robot interaction. His primary research areas include tumor localization during minimally invasive surgery, subcutaneous blood vessel detection, and data collection frameworks for robot learning. Kapadia’s most impactful contribution is the development of automated palpation techniques using Gaussian Process Adaptive Sampling, which enables precise estimation of embedded tumor geometry during robot-assisted surgery—a method that has garnered 73 citations. He also designed a single-use haptic palpation probe for locating blood vessels in robot-assisted minimally invasive surgery (RMIS), a low-cost innovation cited 70 times. This probe uses a Hall Effect sensor to measure tip deflection, offering a practical solution for avoiding vascular damage during procedures. Beyond surgical applications, Kapadia created EchoBot, a system that interfaces the Amazon Echo with an ABB YuMi robot to facilitate intuitive, speech-based data collection for Learning from Demonstration. This work, with 13 citations, highlights his interest in making robot learning more accessible. Kapadia’s contributions advance both the precision of surgical robotics and the efficiency of human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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