Tianyang Tao

Nanjing University of Science and Technology, Université Paris-Saclay

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About

Tianyang Tao is a researcher whose work bridges the critical domains of high-precision 3D optical metrology and advanced artificial intelligence. His primary research areas include real-time 3D shape measurement, fringe projection profilometry, and multi-task deep reinforcement learning. Tao’s most influential contribution is his pioneering work on a bi-frequency scheme combined with a multi-view system for high-speed, high-precision 3D shape measurement. This work, which has garnered 57 citations, directly addresses the inherent trade-offs in conventional multi-frame phase-shifting techniques, enabling robust automatic online inspection and robotics control. More recently, Tao has ventured into AI, introducing PiCor—a novel multi-task deep reinforcement learning framework that tackles the challenge of negative gradient interference between tasks. By implementing a policy correction mechanism, PiCor significantly improves learning efficiency for generalist agents. This forward-looking work, already accumulating 10 citations since 2023, demonstrates Tao’s versatility and his ability to solve complex, cross-disciplinary optimization problems. His research portfolio showcases a unique ability to advance both hardware-driven measurement systems and software-driven learning algorithms, marking him as a rising talent in intelligent systems and automation.