Yotam Barnoy
Papers
8
Total Citations
83
H-Index
7
About
Yotam Barnoy is a robotics researcher whose work sits at the intersection of magnetic surgical robotics, autonomous control, and reinforcement learning. His most significant contributions focus on advancing tetherless, ultra-minimally invasive surgical systems — robotic platforms that eliminate physical connections between actuators and surgical tools by harnessing magnetic fields. His pioneering MPACT-Needle work tackled one of the field's most stubborn challenges: the inverse relationship between robot miniaturization and magnetic force output. By engineering magnetic pulse-actuated collisions, Barnoy's system achieved a remarkable 22.7-fold increase in force without scaling up the device, a breakthrough that has garnered over 20 citations and opened new possibilities for tissue-penetrating interventions. Beyond hardware innovation, Barnoy has made meaningful strides in intelligent surgical control, developing closed-loop magnetic actuation systems with low-error numerical models and applying reinforcement learning to autonomous surgical robot operation — including a lean RL framework designed to overcome the chronic shortage of high-quality surgical training data. His needle localization research further demonstrates a commitment to real-world clinical applicability, addressing the messy realities of blood and tissue in surgical environments. Collectively, his work positions him as an emerging voice in the future of intelligent, miniaturized surgical robotics.
Research Focus
Key Achievements
Top Papers
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- 4Robotic Surgery With Lean Reinforcement Learning10 citations · 2021
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- 7Visual Robot Task Planning8 citations · 2019
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