Xiaofei Shen

Chinese Academy of Sciences, Nanjing Drum Tower Hospital

Papers

Total Citations

H-Index

About

Xiaofei Shen is a pioneering researcher at the intersection of robotic dexterous manipulation and surgical innovation. His primary research areas encompass dexterous grasping, point cloud-based deep learning for robotics, and the clinical application of robotic-assisted surgery. Shen’s major contributions include advancing human-like dexterous manipulation for anthropomorphic hand-arm robotic systems through teleoperation, enabling robots to perform complex, human-like tasks in daily life and industry. His most cited work, “Robotics Dexterous Grasping: The Methods Based on Point Cloud and Deep Learning” (2021), has garnered 58 citations, establishing a foundational framework for integrating point cloud data with deep learning to enhance robotic grasping precision. Additionally, Shen has made notable strides in surgical robotics, as evidenced by his 2022 study comparing robotic-assisted and laparoscopic gastrectomy guided by carbon nanoparticle suspension injection, which achieved 8 citations and highlights his commitment to improving perioperative safety and efficacy. His 2023 work on teleoperated dexterous manipulation further underscores his impact, pushing the boundaries of robotic autonomy. Shen’s research not only bridges robotics and medicine but also inspires future innovations in assistive technologies and minimally invasive surgery.