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.