Zonghe Chua
Papers
7
Total Citations
76
H-Index
5
About
Zonghe Chua is a robotics and biomedical engineering researcher whose work sits at the intersection of haptics, robot-assisted minimally invasive surgery (RMIS), and surgical training. His research addresses two fundamental challenges in modern surgical robotics: restoring meaningful force feedback to surgeons operating through teleoperated systems, and developing effective training paradigms that accelerate skill acquisition. Chua has made notable contributions to force estimation, demonstrating how deep learning and vision-based approaches can infer interaction forces without requiring complex in-vivo sensors — a significant practical advance for clinical deployment. His 2022 paper on neural network-based real-time haptic feedback (13 citations) and his earlier deep learning force estimation work highlight his commitment to bridging algorithmic innovation with physical robotic systems. Equally impressive is his development of a 4-DoF origami haptic device (25 citations), showcasing creativity in fabrication methods to deliver nuanced normal, shear, and torsional fingertip feedback. His investigations into haptic guidance and error amplification for surgical training further reflect a human-centered perspective on robotic systems. Collectively, Chua's portfolio of work — accumulating over 75 citations — positions him as a rising contributor shaping the future of safe, intelligent, and trainable surgical robotics.
Research Focus
Key Achievements
Top Papers
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