Keynote Speakers
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.
Prof. Mingguo Zhao
Tsinghua University, China
BIO: Mingguo Zhao is a professor in the Department of Automation at Tsinghua University. He received a Silver Medal at the Geneva International Exhibition of Inventions in 2017, an Excellence Award in Engineering Education, NI Engineering Impact Awards, was a finalist in the NI Global Student Design Showcase, won first prize at the 23rd International Joint Conference on Artificial Intelligence, and got a best paper finalist at the 2012 IEEE International Conference on Mechanics and Automation. His current research interests include the integration of "brain-inspired chips" and "brain-inspired computing" to build a research platform for artificial general intelligence.
Speech Title: Kicking Like Humans: Legged Embodied-intelligence of Humanoid Robots
Abstract: The development of humanoid robots has a long history and has now become an important new industry that will affect many aspects of human society in the future. In 1997, when IBM's Deep Blue computer defeated the human chess world champion, the field of artificial intelligence proposed that a humanoid robot should beat the human world champion in real football as a landmark technical challenge to promote the development of artificial intelligence and robotics. The international RoboCup competition, undertaking this task, has been developing for almost 30 years. In recent years, the rapid progress of embodied intelligence technology, a concept that refers to the ability of a system to perceive and act in its environment-embodied AI, has promoted the realization of this ambitious goal. In this talk, several technological achievements in the development of humanoid robots are summarized first. Then, the Tsinghua Hephaestus robot soccer team practices and the latest progress of the RoboCup 2024 humanoid league competition are discussed. Finally, it delves into the embodied intelligence methods and the future development directions of humanoid robots, from multimodal perception to agile foot movement.
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.
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. Tianju Sui
Dalian University of Technology, China
BIO: Tianju Sui is a professor and doctoral supervisor at the School of Control Science and Engineering at Dalian University of Technology. Currently, he serves as the director of the Industrial Equipment Monitoring and Control Engineering Research Center of the Ministry of Education. His primary research interests include security protection of cyber-physical systems, industrial Internet of Things (IIoT) technology, and fault diagnosis. He has conducted in-depth theoretical research and extensive engineering applications in these areas. Sui has published 10 papers in the top journals of control theory, including AUTOMATICA and IEEE Transactions on Automatic Control (IEEE TAC), of which he was the first author or corresponding author for 9 papers, including 5 long papers. He has been honored with the AUTOMATICA Most Cited Articles Award and the Best Paper Award at IEEE ICCA (awarded to two papers annually). As the project leader, he has led projects totaling over 40 million RMB, including projects funded by the National Key Research and Development Program. He has been supported by various talent programs such as the National Excellent Youth Fund, the Liaoning Province Xingliao Talent Plan for Outstanding Young Talents, the Dalian Youth Science and Technology Star, and the Xinghai Youth Talent Program. His related technologies have been applied in units such as the National Industrial Information Security Center, Anheng Information, Eastern Communications, and Shandong Luneng, protecting a large number of assets in major projects. Over the past two years, intellectual property rights conversion has yielded 5.3 million RMB through patent licensing.
Speech Title: The Security Theory for Cyber-Physical Systems and Its Applications
Abstract: Facing the security challenges of cyber-physical systems, we first conducted theoretical analysis on their vulnerabilities: for a general model of random linear systems, considering covert attacks on both sensors and actuators, we investigated which system structures would pose risks of state divergence, terming such systems as vulnerability systems. Based on the theory of reachable invariant sets, we theoretically obtained the necessary and sufficient conditions for the vulnerability of random linear systems. Furthermore, we provided an upper bound on state deviation under covert attacks for non-vulnerable systems, quantitatively characterizing the destructive effects of attacks on system performance. In addition to theoretical work, we also constructed a hybrid industrial Internet of Things (IIoT) security testbed and conducted extensive engineering experiments on security monitoring and defense, achieving certain results.