Rui Yang received the B.Eng. degree in Computer Engineering and the Ph.D. degree in Electrical and Computer Engineering from National University of Singapore. He is currently an Associate Professor in the School of Advanced Technology, Xi’an Jiaotong-Liverpool University, Suzhou, China, and an Honorary Lecturer in the Department of Computer Science, University of Liverpool, Liverpool, United Kingdom. His research interests include machine learning based data analysis and applications. He is the author or co-author of several technical papers and also a very active reviewer for many international journals and conferences. Dr. Yang is currently serving as an Associate Editor for Neurocomputing and International Journal of Network Dynamics and Intelligence.
Abstract: This talk will introduce a brain-computer interface motor imagery classification method based on deep transfer learning, as well as the independently developed open-source tool EEGUnity for unified EEG datasets. First, to address the problem of cross-subject transfer from a single source domain to a single target domain, we designed a multi-subdomain adaption network method to solve the problem of time-related distribution shift of EEG data. At the same time, in response to the challenges brought by the variability of EEG data content and format to EEG large models, we designed an open source tool EEGUnity that achieves efficient management of datasets from different sources through intelligent integration of structural reasoning, data cleaning and unification, and provides a reliable foundation for the study of EEG large models.
Xie Ming received the B.Eng degree in control and automation engineering from East-China Institute of Textile Technology (now, under the name of Donghua University, Shanghai, China). Subsequently, as a recipient of the nation's prestigious overseas scholarship of Chinese government, he has completed the postgraduate studies and doctorate research works, and has received the Master degree from the University of Valenciennes (France) in 1986 as well as the PhD degree from the University of Rennes (France) in 1989. Since 1986, he has worked as Research Assistant at IRISA-INRIA Rennes, Expert Engineer at INRIA Sophia-Antipolis, Lecturer/Senior Lecturer/Associate Professor of Nanyang Technological University, Fellow of Singapore-MIT Alliance (SMA) (Affiliated with Innovation in Manufacturing Systems and Technology Program), Guest Professor of Huazhong University of Science and Technology (2002, 2006), Professor awarded by China's Jiangsu Provincial Government (2014), and Dean of College of Electrical Engineering and Control Science at Nanjing Tech University (2014-2016). He was the General Chair of 2007 International Conference on Climbing and Walking Robots (CLAWAR), the General Chair of 2009 International Conference on Intelligent Robotics and Applications (ICIRA), the Co-founder of the International Journal of Humanoid Robotics (SCI/SCIE indexed), Co-founder of Singapore-China Association for Advancement of Science and Technology, Co-founder of Robotics Society of Singapore. He has taught the courses such as Robotics, Artificial Intelligence, Applied Machine Vision, Measurement and Sensing Systems, Microprocessor Systems, and University Physics. In terms of scientific research, he has authored three books in English, two books in Chinese, and two edited books in English. He has published several book chapters, over 10 patents of invention, over 40 research papers in scientific journals and over 100 research papers in international conferences. He was the recipient of one best conference paper award from World Automation Congress, the recipient of one best conference paper award from CLAWAR, the recipient of one outstanding paper award from International Journal of Industrial Robot, the recipient of one Gold Prize (S$8K) from CrayQuest, the recipient of one Grand Champion Prize (S$15K) from CrayQuest, the recipient of one A-Star's Best Research Idea Prize (S$5K), the recipient of one Silver Medal from Dragon Design Foundation.
Abstract：Does intelligence arise from brain or mind? The wrong answer to this question has led the research efforts into the wrong direction in the past decades. In this keynote speech, I will convince the audience about the astonishing truth which is to say that intelligence arises from mind but not from brain. This truth leads us to open the door toward achieving the science of mind which will be the new foundation of Artificial Intelligence. We know that Artificial Intelligence is regaining its wide popularity in recent years. On one hand, the importance of Artificial Intelligence is due to the availability of big data which is the result of the formation of large systems that are interconnected by various networks. On the other hand, robots and machines of tomorrow are urgently in need of gaining self-intelligence which will enable them to efficiently perform difficult tasks, and even to free people from doing dangerous jobs. With the rise of Artificial Intelligence in the public minds or eyes, people are putting a very high level of interests on knowing the scientific solutions behind the understanding and capabilities of self-skills and self-intelligence. Hopefully, this keynote speech will help the audience to understand the true nature of Artificial Intelligence which interestingly establishes the foundation of the Science of Mind.