Prof. Nikhil Pal, the Indian Statistical Institute, India
Bio: Nikhil R. Pal (www.isical.ac.in/~nikhil) is an INAE Chair Professor in the Electronics and Communication Sciences Unit of the Indian Statistical Institute. His current research interest includes bioinformatics, brain science, fuzzy logic, neural networks, machine learning, and data mining. He was the Editor-in-Chief of the IEEE Transactions on Fuzzy Systems (January 2005-December 2010). He has served/been serving on the editorial /advisory board/ steering committee of several journals including the International Journal of Approximate Reasoning, Applied Soft Computing, Fuzzy Sets and Systems, Fuzzy Information and Engineering : An International Journal, IEEE Transactions on Fuzzy Systems and the IEEE Transactions on Systems Man and Cybernetics B (currently IEEE Transactions on Cybernetics). He is a recipient of the 2015 Fuzzy Systems Pioneer Award. He has given many plenary/keynote speeches in different premier international conferences in the area of computational intelligence. He has served as the General Chair, Program Chair, and co-Program chair of several conferences. He was a Distinguished Lecturer of the IEEE Computational Intelligence Society (CIS) and was a member of the Administrative Committee of the IEEE CIS. At present he is the Vice President for Publications of the IEEE CIS. He is a Fellow of the National Academy of Sciences, India; the Indian National Academy of Engineering; the Indian National Science Academy, the International Fuzzy Systems Association (IFSA), and IEEE, USA.
Prof. Dongrui Wu, Huazhong University of Science and Technology, China
Bio: Dongrui Wu (IEEE Fellow) received a B.E in Automatic Control from the University of Science and Technology of China, Hefei, China, in 2003, an M.Eng in Electrical and Computer Engineering from the National University of Singapore in 2006, and a PhD in Electrical Engineering from the University of Southern California, Los Angeles, CA, in 2009. He is now Chair Professor and Vice Dean of School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China. His research interests include brain-computer interface and machine learning. He has more than 200 publications (17000+ Google Scholar citations; h=69), with 7 outstanding paper awards. His team won National Champion of the China Brain-Computer Interface Competition in seven successive years (2019-2025). He is the Editor-in-Chief of IEEE Transactions on Fuzzy Systems.
Speech Title: Machine Learning in Brain-Computer Interfaces
Abstract: A brain-computer interface (BCI) enables direct communication between the brain and external devices. 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 decoding. Additionally, adversarial security and privacy protection are also very important to the broad applications of BCIs. This talk will introduce machine learning algorithms for accurate, secure and privacy-preserving BCIs.