Prof. Qinmin Yang
Zhejiang University, China
BIO: Qinmin Yang received the Bachelor's degree in Electrical Engineering from Civil Aviation University of China, Tianjin, China in 2001, the Master of Science Degree in Control Science and Engineering from Institute of Automation, Chinese Academy of Sciences, Beijing, China in 2004, and the Ph.D. degree in Electrical Engineering from the University of Missouri-Rolla, MO USA, in 2007.
From 2007 to 2008, he was a Post-doctoral Research Associate at University of Missouri-Rolla. From 2008 to 2009, he was an advanced system engineer with Caterpillar Inc. From 2009 to 2010, he was a Post-doctoral Research Associate at University of Connecticut. Since 2010, he has been with the State Key Laboratory of Industrial Control Technology, the College of Control Science and Engineering, Zhejiang University, China, where he is currently a professor. He has also held visiting positions in University of Toronto and Lehigh University. He has been serving as an Associate Editor for IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Neural Networks and Learning Systems, Transactions of the Institute of Measurement and Control, Processes, and Automatica Sinica. His research interests include intelligent control, renewable energy systems, smart grid, and industrial big data.
Speech Title：Theoretical Research and Practice in Intelligent Control Design for Wind Energy
Abstract： Wind energy has been considered to be a promising alternative to current fossil-based energies. Large-scale wind turbines have been widely deployed to substantiate the renewable energy strategy of various countries. In this talk, challenges faced by control community for high reliable and efficient exploitation of wind energy are discussed. Advanced controllers are designed to (partially) overcome problems, such as uncertainty, intermittence, and intense dynamics. Theoretical results and attempts for practice are both present.
Prof. Genci Capi
Hosei University, Japan
BIO: Genci Capi received the Ph.D. degree from Yamagata University, in 2002. He was a Researcher at the Department of Computational Neurobiology, ATR Institute from 2002 to 2004. In 2004, he joined the Department of System Management, Fukuoka Institute of Technology, as an Assistant Professor, and in 2006, he was promoted to Associate Professor. He was a Professor in the Department of Electrical and Electronic Systems Engineering, at the University of Toyama up to March 2016. Now he is a Professor in the Department of Mechanical Engineering, Hosei University. His research interests include intelligent robots, BMI, multi-robot systems, humanoid robots, learning and evolution.
Speech Title: Toward Human-Robot Collaboration Based on EEG-EMG Signals
Abstract: Human-robot collaboration is crucial as robots are getting closer to humans. Most of the previous research works are focused on human-robot collaborations using natural language and gesture recognition. However, it will be useful to have robots that understand human intentions. This keynote speech delves into the emerging field of human-robot collaboration (HRC) through the innovative use of EEG (Electroencephalography) and EMG (Electromyography) signals. As robotics technology advances, the integration of brain and muscle signals opens new frontiers for seamless interaction between humans and machines. By using EEG and EMG data, we can create more intuitive and responsive robots that understand and adapt to human intentions and physical states in real time. This talk will explore the underlying principles, recent breakthroughs, and potential applications of EEG-EMG-based HRC, offering insights into how this technology can improve productivity, safety, and human well-being across various domains. This talk will present the recent research results conducted at Human Assistive Robotics Lab., Hosei University. In addition, future directions in developing robots that not only coexist with humans but also collaborate with them will be discussed.