Papers
8
Total Citations
111
H-Index
5
About
Yingxuan Zhang is a robotics and biomedical engineering researcher whose work sits at the intersection of surgical robotics, tactile sensing, and minimally invasive surgery. Their research has made significant contributions to advancing robot-assisted minimally invasive surgery (RMIS) by addressing one of its most persistent limitations: the absence of meaningful tactile feedback during surgical procedures. Zhang's most impactful work focuses on piezoelectric tactile sensors capable of detecting tissue stiffness and identifying tumors intraoperatively, with their 2020 paper on angle-independent stiffness detection earning 33 citations. Building on this, they developed dual-mode tactile sensors and palpation-based multi-tumor detection methods that bring the nuanced judgment of manual palpation into robotic systems. Complementing this sensing expertise, Zhang has also designed miniature continuum robots for challenging anatomical environments, including transnasal skull base surgery, accumulating 27 citations for that contribution alone. More recently, Zhang has integrated deep reinforcement learning with tactile array sensors to enable autonomous tumor detection and resection path planning, pointing toward truly intelligent surgical systems. With a total citation count exceeding 110 across eight papers, Zhang's body of work represents a cohesive and growing vision for safer, more perceptive surgical robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2Design and analysis of a continuum robot for transnasal skull base surgery27 citations · 2021
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- 7Design and Analysis of a Micro Flexible Surgical Robot4 citations · 2021
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