Cheng-Lin Liu (Fellow, IEEE) received the B.S. degree in Electronic Engineering from Wuhan University, Wuhan, China, in 1989, the M.E. degree in Electronic Engineering from the Beijing University of Technology, Beijing, China, in 1992, and the Ph.D. degree in Pattern Recognition and Intelligent Control from the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, in 1995.

He was a postdoctoral fellow with the Korea Advanced Institute of Science and Technology (KAIST) and later with the Tokyo University of Agriculture and Technology from March 1996 to March 1999. From 1999 to 2004, he was a research staff member and later a senior researcher with the Central Research Laboratory, Hitachi, Ltd., Tokyo, Japan. Since 2005, he has been a Professor with the Institute of Automation, CAS.

His research interests include pattern recognition, machine learning, document analysis and recognition. He has published more than 400 technical papers in prestigious international journals and conferences.

He serves as Associate Editor-in-Chief of the Pattern Recognition Journal and Acta Automatica Sinica, and is on the editorial board of several international and domestic journals. He is a Fellow of the IAPR, the CAA, and the CAAI.

Yaochu Jin (Fellow, IEEE, Member of Academia Europaea) is the President of the IEEE Computational Intelligence Society (CIS) and Editor-in-Chief of Complex & Intelligent Systems. He previously served as Editor-in-Chief of the IEEE Transactions on Cognitive and Developmental Systems, and as an IEEE Distinguished Lecturer in 2013–2015 and 2017–2019. He was Vice President for Technical Activities of IEEE CIS (2015–2016).

Prof. Jin is the recipient of the 2018, 2021 and 2023 IEEE Transactions on Evolutionary Computation Outstanding Paper Award, and the 2015, 2017, and 2020 IEEE Computational Intelligence Magazine Outstanding Paper Award. He was named a Highly Cited Researcher by Clarivate consecutively from 2019, and received the 2025 IEEE Frank Rosenblatt Award.

His research covers evolutionary computation, neural self-organisation, swarm intelligence, computational modeling of complex systems, and trustworthy AI-driven optimization. He has made influential contributions to data-driven evolutionary optimization, multi-objective learning, and biologically inspired self-organizing systems.

Professor Irwin King is a globally recognized scholar in machine intelligence, currently serving as the Pro-Vice-Chancellor (Education) and Professor at the Department of Computer Science & Engineering, The Chinese University of Hong Kong (CUHK). His extensive research interests cover trustworthy AI, machine learning, social computing, AI for education, and data mining. He is a Fellow of ACM, IEEE, INNS, AAIA, and HKIE.

Professor King has assumed numerous leadership roles in prominent conferences and societies. He was President of the International Neural Network Society (INNS), and General Co-chair for major conferences including WebConf 2020, ICONIP 2020, ACML 2015, RecSys 2013, and WSDM 2011. He has also served in leadership capacities in conferences such as WWW, NeurIPS, ICML, IJCAI, AAAI, and ICONIP. He currently serves as Vice-President of the ACM SIGWEB, Vice-President of the WebConf Steering Committee, and a board member of INNS and the Asia Pacific Neural Network Society (APNNS).

He has received numerous prestigious awards recognizing his contributions, including the 2021 INNS Dennis Gabor Award for engineering applications of neural networks, the 2020 APNNS Outstanding Achievement Award, and several Test of Time Awards from top ACM conferences such as CIKM 2019, SIGIR 2020, and WSDM 2022. During his sabbatical at AT&T Labs Research in San Francisco, he was a Visiting Professor and taught at UC Berkeley.

Professor King is Director of the Centre for Learning Innovation and Technology (ELITE), which promotes eLearning and education technology, and leads the Machine Intelligence and Social Computing (MISC) Lab focusing on machine learning and social computing research. He holds a B.Sc. in Engineering and Applied Science from Caltech, and an M.Sc. and Ph.D. in Computer Science from the University of Southern California (USC).