Ying Tan

Professor Ying Tan is a Professor and Reader in the Department of Mechanical Engineering within the Faculty of Engineering and Information Technology at the University of Melbourne. She obtained her Bachelor's degree and Master's degree by research from Tianjin University, China, and her PhD from the National University of Singapore in 2002. After completing a postdoctoral fellowship at McMaster University, Canada, she joined the University of Melbourne in 2004, advancing through academic ranks to her current position. Tan's research specializations include control engineering, intelligent systems, nonlinear systems, data-driven optimization, rehabilitation robotics, human motor learning, wearable sensors, and model-guided machine learning. She has authored over 100 journal articles, amassed more than 10,000 citations on Google Scholar, and secured over $7 million AUD in research funding. As co-leader of the Human Robotics Laboratory since 2017, she develops rehabilitation robots for movement recovery post-stroke or injury, smart prosthetics, and human-robot collaboration technologies. Since 2018, she has co-directed an industry-academic joint laboratory with Fourier Intelligence, resulting in the commercialization of the award-winning ArmMotus™ EMU device, now utilized in hospitals across Asia, the US, and the UK.

Tan has earned prestigious honors, including the Australian Postdoctoral Fellowship (2006-2008), ARC Future Fellowship (2009-2013), IEEE Fellowship in 2023 for contributions to rehabilitation robotics, Fellowship of Engineers Australia (FIEAust), Fellowship of the Asia-Pacific Artificial Intelligence Association, and Fellowship of the Australian Academy of Technological Sciences and Engineering (ATSE) in 2025 for pioneering learning control in robotics innovation. She currently serves on the Australian Research Council College of Experts (2024-2026) and the IEEE Fellow Committee (2024-2025). Key publications include the book Linear and Nonlinear Iterative Learning Control (Springer, 2003, with J.X. Xu) and the paper 'On non-local stability properties of extremum seeking control' (Automatica, 2006, with D. Nešić and I. Mareels). Her work has significantly impacted the fields of control systems and biomedical robotics through fundamental research, applied developments, and successful technology transfer.

Professional Email: yingt@unimelb.edu.au