Max Robotics — Global Service Robot Directory + US Certification

About

Xuan Thao Ha is at the forefront of integrating artificial intelligence with flexible surgical robotics, with a primary focus on enhancing the safety and precision of minimally invasive cardiovascular interventions. His research centers on deep learning for shape sensing, compliant motion control, and contact localization in continuum robots like robotic catheters. Ha’s major contributions include pioneering a deep-learning method for shape sensing using multicore fiber Bragg grating fibers, achieving accurate 3D reconstruction of flexible robots without complex traditional models. He also developed a deep-learning-based compliant motion control system for pneumatically-driven catheters, enabling safer navigation by preventing excessive force on vessel walls. His work on data-driven contact localization allows clinicians to estimate both the location and magnitude of forces exerted by flexible instruments, a critical step toward autonomous or semi-autonomous catheter guidance. With over 150 citations across his most-cited papers—including a comprehensive 2024 review on machine learning in flexible surgical robots—Ha’s research is shaping the next generation of intelligent, safer interventional tools. His comparative analysis of interactive modalities for endovascular interventions further underscores his commitment to translating AI-driven robotics into practical clinical solutions.