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About

Haoying Zhou is an emerging researcher at the intersection of surgical robotics, computer vision, and medical imaging, with a focus on advancing the perception and automation capabilities of robot-assisted surgical systems. His work spans several interconnected areas, including photoacoustic imaging integration, surgical tool tracking and pose estimation, haptic feedback, and learning-based autonomy for robotic surgery. Among his most impactful contributions is the development of a laparoscopic photoacoustic imaging framework integrated with the da Vinci surgical system, which combines the high penetration of ultrasound with rich optical contrast to provide intraoperative guidance — work that has already garnered 16 citations since 2023. Complementing this, Zhou has pioneered deep learning approaches for markerless suture needle tracking and 6D pose estimation of surgical instruments, addressing critical perception bottlenecks in surgical automation. His creation of SurgPose, a dedicated dataset for articulated robotic tool pose estimation, reflects a commitment to enabling reproducible research across the community. Zhou also contributes to simulation and policy learning environments, including NVIDIA Isaac Sim-based surgical frameworks and the SurgicAI benchmarking platform. With over 40 cumulative citations across his growing portfolio, his research is steadily shaping the future of intelligent, autonomous robotic surgery.