Speakers 2024
Keynote Speaker Ⅰ
| Speech Title: To be updated | |
| Prof. Fuchun Sun IEEE Fellow, CAAI Fellow and CAA Fellow Tsinghua University, China |
Biography: Dr. Fuchun Sun is a full professor, and vice director in the academic tenure committee of department of computer science and technology, director of intelligent robot center of AI research academy, Tsinghua University. He also serves as Vice president of China artificial intelligence society and executive director of China automation society. His research interests include robotic perception and intelligent control. He has won the Champion of Autonomous Grasp Challenges in IROS2016 and IROS 2019. Dr. Sun is the recipient of the excellent Doctoral Dissertation Prize of China in 2000 by MOE of China and the Choon-Gang Academic Award by Korea in 2003, and was recognized as a Distinguished Young Scholar in 2006 by the Natural Science Foundation of China. He is elected as IEEE Fellow and CAAI Fellow in 2019, CAA Fellow in 2020.He served as an associated editor of IEEE Trans. on Neural Networks during 2006-2010, IEEE Trans. On Fuzzy Systems during 2011-2018, IEEE Trans. on Cognitive and Development since 2018 and IEEE Trans. on Systems, Man and Cybernetics: Systems since 2015. He was invited to make a plenary talk or keynote speech at the international summit ICRA 2021, IROS 2019, AAAI 2021, etc.
Abstract: To be updated
Keynote Speaker Ⅱ
| Speech Title: Machine Learning for Brain-Computer Interfaces | |
| Prof. Dongrui Wu IEEE Fellow Huazhong University of Science and Technology, China |
Biography: Dongrui Wu (IEEE Fellow) is Professor and Deputy Director of the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China. Prof. Wu's research interests include brain-computer interface, machine learning, computational intelligence, and affective computing. He has more than 200 publications (12000+ Google Scholar citations; h=57). He received the IEEE Computational Intelligence Society Outstanding PhD Dissertation Award in 2012, the IEEE Transactions on Fuzzy Systems Outstanding Paper Award in 2014, the IEEE Systems, Man and Cybernetics Society Early Career Award in 2017, the USERN Prize in Formal Sciences in 2020, the IEEE Transactions on Neural Systems and Rehabilitation Engineering Best Paper Award in 2021, the Chinese Association of Automation (CAA) Early Career Award in 2021, the Ministry of Education Young Scientist Award in 2022, and First Prize of the CAA Natural Science Award. His team won National Champion of the China Brain-Computer Interface Competition in two successive years (2021-2022). Prof. Wu is the Editor-in-Chief of IEEE Transactions on Fuzzy Systems.
Abstract: A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. Electroencephalograms (EEGs) used in BCIs are weak, easily contaminated by interference and noise, non-stationary for the same subject, and varying across different subjects and sessions. Thus, sophisticated machine learning approaches are needed for accurate and reliable EEG-based BCIs. This talk will introduce the basic concepts of BCIs, review the latest progress, and describe several newly proposed machine learning approaches for BCIs.
Keynote Speaker Ⅲ
| Speech Title: A Systematic Approach to Wearable Roboticd Development | |
| Assoc. Prof. Haoyong Yu National University of Singapore, Singapore |
Biography: Dr. Yu Haoyong is an Associate Professor of the Department of Biomedical Engineering at the National University of Singapore. He received his Bachelor’s Degree and Master’s Degree from Shanghai Jiao Tong University and his PhD degree from Massachusetts institute of Technology (MIT). His current research interests include biomedical robotics and devices, rehabilitation engineering and assistive technology, service robots, human robot interaction, intelligent control and machine learning. Dr. Yu is the Associate Editor of IEEE Transactions on Automation Science and Engineering and IEEE/ASME Transactions on Mechatronics.
Abstract: With the rapid population aging, wearable Robotics, commonly known as Exoskeleton Robots, are believed to have great potential applications in many areas in both industry and Healthcare. However, the current market size of wearable robotics is still quite small compared with other robotics sectors due to the limitations in design, user experience, and high cost. At NUS Biorobotics Lab, we are developing a series of wearable robotics with wide range applications. We adopt a modular approach based a set of core technologies and components developed in the lab, which includes compliant actuation, cable mechanism, wearable sensors and learning based movement detection algorithms. We achieved better portability and better human robot interaction due to our compliant actuation and cable transmission and novel mechanism design. In this talk, we will give a brief introduction of some of our wearable robots and their potential applications.
More speakers are to be announced......