Zhi Hu

Shanghai University of Engineering Science

Papers

Total Citations

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About

Zhi Hu is a pioneering researcher in the field of robotic-assisted cardiovascular and vascular interventional surgery, with a focus on enhancing precision and transparency in master-slave surgical systems. His key research areas include predictive control for remote surgical systems and unsupervised learning for guidewire shape registration. Hu’s major contribution lies in developing a generalized predictive control framework for remote cardiovascular surgical systems, which addresses time delays and improves stability in teleoperation—a critical advancement for minimally invasive procedures. This work has garnered 17 citations, reflecting its impact on surgical robotics. More recently, Hu introduced an unsupervised learning-based method for guidewire shape registration in vascular interventional surgery robots (VISR), tackling the challenge of deformation-induced inaccuracies during navigation. By enabling more precise guidewire manipulation within blood vessels, this innovation enhances the safety and efficacy of robot-assisted vascular interventions. Hu’s research bridges control theory and machine learning, offering practical solutions for real-time, high-transparency surgical systems. His work is particularly notable for its potential to improve patient outcomes in complex cardiovascular and vascular procedures, positioning him as a rising contributor to the intersection of robotics, control, and medical technology.