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About

Tianbao He is a leading researcher in medical robotics, specializing in the automation of venipuncture—a critical yet challenging clinical procedure. His work integrates deep learning, near-infrared vision, and biomechanical modeling to create intelligent, fully autonomous venipuncture robots. He’s best known for developing a novel robot with decoupled position and attitude control, guided by near-infrared vision and force feedback, which significantly enhances puncture accuracy and safety. His 2021 paper on automatic venous segmentation using deep learning (13 citations) laid the groundwork for real-time vein identification, while his 2022 study on multiobjective optimization for puncture site selection (12 citations) advanced decision-making in robotic systems. He also pioneered a humanoid venipuncture method based on a biomechanical model (10 citations) and explored electrical impedance for real-time puncture status perception. With over 47 total citations, He’s contributions are directly addressing the need to reduce healthcare worker workload and infection risk, particularly highlighted during the COVID-19 pandemic. His work represents a significant step toward making robotic venipuncture a reliable, everyday clinical tool.