International Eurasian Academy of Sciences, IEAS

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Yongduan SONG
Academician
Yongduan SONG
Profile:
Elected Academician of the International Eurasian Academy of Sciences in 2019, Professor Yongduan Song is a distinguished Chinese control scientist and artificial intelligence researcher whose research and professional work have focused on intelligent control, adaptive control, fault-tolerant control, and intelligent robotic systems. Born in June 1962 in Changshou, Chongqing, he received his B.S. from Sichuan University in 1983, his M.S. from Chongqing University in 1986, and his Ph.D. in Electrical and Computer Engineering from Tennessee Technological University, USA, in 1992, following doctoral studies at Beihang University and the University of Newcastle, Australia. From 1993 to 2008, he held a tenured full professorship at North Carolina Agricultural and Technical State University and, from 2005 to 2008, served as one of the six Langley Distinguished Professors and Founding Director of the Center for Cooperative Systems at the National Institute of Aerospace, USA. He returned to China in 2008 as a Professor at Beijing Jiaotong University and served as Dean of the School of Automation at Chongqing University from 2012 to 2022, where he currently serves as Director of the Artificial Intelligence Research Institute. In November 2025, he was elected a Foreign Member of the Chinese Academy of Engineering. He currently serves as Dean of the School of Data Science and Chair Professor of Industrial Data Science at Lingnan University. He is a Fellow of IEEE, the Chinese Association for Artificial Intelligence, and the Chinese Association of Automation, and has been included in Stanford University’s list of the world’s top 2% of scientists and Clarivate’s Highly Cited Researchers.

Professor Song’s research has centred on intelligent control, fault-tolerant control, adaptive coordinated control, and neural network-based control of nonlinear systems, with applications in robotics, autonomous unmanned systems, swarm intelligence, biomimetic intelligent control, and renewable energy systems. Through national research programmes, including the National 973 Programme, the National 863 Programme, and the National Key Research and Development Programme, he has contributed to the development of adaptive neural-network control methods and their engineering applications. He has authored twelve monographs and more than 400 peer-reviewed publications, including articles in IEEE Transactions on Automatic Control, Automatica, and IEEE Transactions on Neural Networks and Learning Systems, and holds approximately 100 authorised invention patents in China, the United States, and Japan. His academic service has included serving as Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems and Founding Editor-in-Chief of the Journal of Automation and Intelligence. Through sustained research, academic leadership, and international collaboration, Professor Song has contributed to connecting advances in control theory and artificial intelligence with practical applications in autonomous systems, intelligent robotics, renewable energy, and intelligent manufacturing.