主題演講

Brain-Computer Interface (BCI) enhances the capability of a human brain in communicating and interacting with the environment directly. BCI plays an important role in natural cognition, which is to study the brain and behavior at work. Human cognitive functions such as action planning, intention, preference, perception, attention, situational awareness, and decision-making are omnipresent in our daily life activities. BCI has been considered as the disruptive technology for the next-generation human computer interface in wearable computers and devices.

In addition, there are many potential real-life impacts of BCI technology in both daily life applications for augmenting human performance, and daily care applications for elder/patients healthcare in real world and virtual world. Talk focus will be the applications of BCI technology on AR-based brain robot interface, BCI-based assistive glasses for the blind, Biofeedback for chronic pain mitigation, and BCI-based human-machine cooperation. The potential applications of BCI in the coming Metaverse will be also introduced in this talk.

Chin-Teng Lin received the B.S. degree from the National Chiao-Tung University (NCTU), Taiwan in 1986, and the Master and Ph.D. degree in electrical engineering from Purdue University, West Lafayette, Indiana, U.S.A. in 1989 and 1992, respectively. He is currently a Distinguished Professor, Director of UTS Human-centric AI Center, Co-Director of Australian AI Institute, and Director of CIBCI Lab, FEIT, UTS. He is also invited as the International Faculty of the University of California at San Diego (UCSD) from 2012 to 2020 and Honorary Professorship of University of Nottingham from 2014 to 2021.

Prof. Lin's research focuses on machine-intelligent systems and brain computer interface, including algorithm development and system design. He has published over 460 journal papers (H-Index 98 based on Google Scholar) and is the co-author of Neural Fuzzy Systems (Prentice-Hall) and author of Neural Fuzzy Control Systems with Structure and Parameter Learning (World Scientific). Dr. Lin served as Editor-in-Chief of IEEE Transactions on Fuzzy Systems from 2011 to 2016 and has served on the Board of Governors of IEEE Circuits and Systems Society, IEEE Systems, Man, and Cybernetics Society, and IEEE Computational Intelligence Society. He is the Chair of the 2022-2023 CIS Awards Committee. Dr. Lin is an IEEE Fellow and received the IEEE Fuzzy Pioneer Award in 2017. He received the UTS Chancellor's Medal of Research Excellence in 2015.