Keynote SPEAKER 主旨报告

 

Prof. Jie Lu, University of Technology Sydney, Australia
IEEE Fellow, IFSA Fellow, Australian Laureate Fellow, Australian Industry Laureate Fellow
Director of Australian Artificial Intelligence Institute
Director of Australian Research Council Research Hub in Responsible AI for a Sustainable Grain Industry (gRAIn)

Distinguished Professor Jie Lu is a world-renowned scientist in the field of computational intelligence, best known for her contributions to fuzzy machine learning, transfer learning, concept drift, recommender systems, and decision support systems. She is an IEEE Fellow, IFSA Fellow, Australian Laureate Fellow, and Australian Industry Laureate Fellow. Professor Lu is the Director of the Australian Artificial Intelligence Institute (AAII) and Director of Australian Research Council (ARC) Research Hub in Responsible AI for a Sustainable Grain Industry (gRAIn) at the University of Technology Sydney (UTS), Australia. She has published six research books and over 500 papers in leading journals and conferences; won ten ARC Discovery Projects, one ARC Linkage Project as Lead Chief Investigator, an ARC Research Hub in Responsible AI for a Sustainable Grain Industry (gRAIn) as the Director, and over 20 industry-funded projects; and supervised 60 doctoral students to completion. Professor Lu also serves as Editor-in-Chief of Knowledge-Based Systems and the International Journal of Computational Intelligence Systems. She is a highly sought-after keynote speaker and has delivered over 40 keynote addresses at major international conferences. Her honours include three IEEE Transactions on Fuzzy Systems Outstanding Paper Awards (2019, 2022, 2025), the NeurIPS 2022 Outstanding Paper Award, Australia’s Most Innovative Engineer Award (2019), the Australasian Artificial Intelligence Distinguished Research Contribution Award (2022), the NSW Premier’s Prize for Excellence in Engineering or Information and Communication Technology (2023), and appointment as an Officer of the Order of Australia (AO) in the 2023 Australia Day.

Title: Machine Learning for Decision Support in Complex Environments
Abstract: This talk will present how advanced machine learning can innovatively and effectively learn from complex data to support data-driven decision-making in uncertain and dynamic environments. A set of new autonomous transfer learning theories, methodologies, and algorithms will be introduced to enable knowledge transfer from multiple source domains to a target domain through the construction of latent spaces, mapping functions, and self-training mechanisms, thereby addressing substantial uncertainties in data, learning processes, and decision outputs. In addition, a new suite of theories, methodologies, and algorithms for concept drift detection, understanding, and adaptation will be discussed, focusing on how to manage continuously evolving data stream environments with unpredictable pattern changes. These approaches can detect concept drift accurately and in an explanatory manner, identifying when, where, and how drift occurs and enabling timely adaptive responses. These advanced machine learning capabilities have been applied to develop a range of real-world applications across multiple industry sectors, significantly strengthening data-driven prediction and decision support systems.

Prof. Yi Pan, Shenzhen University of Advanced Technology, China
中国科学院深圳理工大学计算机科学与控制工程学院院长、讲席教授、教育部长江学者讲座教授
美国医学与生物工程院院士、英国皇家公共卫生学院院士、英国工程技术学会会士

Yi Pan is currently a Chair Professor and the Dean with the College of Computer Science and Control Engineering, Shenzhen University of Advanced Technology, Shenzhen, China, and a Regents' Professor Emeritus with Georgia State University, Atlanta, GA, USA. From 2005 to 2020, he was the Chair with Computer Science Department, Georgia State University. During 2013–2017, he was also the Interim Associate Dean and Chair with Biology Department. In 2000, he joined Georgia State University, was promoted to Full Professor in 2004, named a Distinguished University Professor in 2013, and Designated a Regents' Professor (the highest recognition given to a Faculty Member by the University System of Georgia) in 2015. He has authored or coauthored more than 450 papers including more than 250 journal papers with more than 100 papers published in IEEE/ACM Transactions/Journals and has also edited/authored 43 books. His work has been cited more than 27000 times based on Google Scholar and his current H-index is 98. Dr. Pan is also the Editor-in-Chief of Big Data Mining and Analytics (a top 3% journal), Associate Editor-in-Chief of Journal of Computer Science and Technology (JCST), and Chinese Journal of Electronics (CJE). He was the Editor-in-Chief or Editorial Board Member for 20 journals including seven IEEE Transactions.

 

 

Prof. Ning Zhong, Web Intelligence Consortium (WIC), Maebashi Institute of Technology, Japan
教育部长江学者讲席教授、日本前桥工业大学名誉教授、日本工程院外籍院士、国际网络智能协会 (WIC) 创办人并任主席

Ning Zhong obtained his Ph.D. from the University of Tokyo. He currently holds positions as the director & chairman of the Web Intelligence Consortium (WIC), CEO & Chief Scientist of the Web Intelligence Lab, Professor Emeritus/Visiting Professor, and previously served as a professor in the Department of Life Science and Informatics at Maebashi Institute of Technology, Japan. Prof. Zhong is a foreign fellow of the Engineering Academy of Japan (EAJ).
Prof. Zhong's present research interests include Web Intelligence (WI), Brain Informatics (BI), Data Mining, Granular Computing, and Intelligent Information Systems. In 2000 and 2004, Zhong and colleagues introduced WI and BI as new research directions, respectively. Currently, he is focusing on "WI meets BI" research with three aspects: (1) systematic investigations for complex brain science problems; (2) BI studies based on WI research needs; and (3) new information technologies for supporting systematic brain science studies. The synergy between WI and BI advances our ways of analyzing and understanding of data, information, knowledge, wisdom, as well as their interrelationships, organizations, and creation processes, to achieve human-level Web intelligence reality. In 2010, Zhong and colleagues extended such a vision to develop Wisdom Web of Things (W2T) as a holistic framework for computing and intelligence in the big data era. Recently Zhong and colleagues have been working on brain big data based wisdom service project, in which the fundamental issues include how brain informatics based big data interacts in the social-cyber-physical space of the W2T and how to realize human-level collective intelligence as a big data sharing mind, a harmonized collectivity of consciousness on the W2T that uses brain-inspired intelligent technologies to provide wisdom services.

 

 

 

 

Prof. Jie Xu, University of Leeds, UK
国家级特聘专家、英国Alan Turing Fellow、CCF 2023海外科技人物奖获得者

Jie Xu is Chair of Computing at the University of Leeds, Director of the UK White Rose Grid e-Science Centre, involving the three White Rose Universities of Leeds, Sheffield and York, a co-Leader of the EPSRC-funded UK National Hub in Clouds and Distributed Computing, and Head of the Distributed Systems and Services (DSS) Theme at Leeds. Xu has worked in the field of Distributed Computing Systems for over forty years, engaging closely with industrial leaders in the field. He received a PhD in Computing Science from the University of Newcastle upon Tyne, and was Professor of Distributed Systems at the University of Durham before joined Leeds in 2003.
Professor Xu is an executive member of UKCRC (UK Computing Research Committee) and a Turing Fellow in AI and Data Science. He has served as an academic expert for numerous governments and industries, such as Singapore IDA, Lenovo, UK EPSRC, UK DTI (InnovateUK), and Research Ireland. In addition, he has extensive editorial experience, having served as an editor for IEEE Distributed Systems from 2000 to 2005, and currently acting as an associate editor of IEEE Transactions on Parallel and Distributed Systems and ACM Computing Surveys. Professor Xu is currently the Steering Committee Chair of IEEE ISADS, a Steering Committee member for several IEEE conferences, such as SRDS, ISORC, HASE, SOSE, JCC, and CISOSE, as well as serving on the steering board of IEEE TC on BIS. He has also been a General Chair/PC Chair for various IEEE international conferences. With over 300 academic publications, including papers in top-ranked IEEE and ACM Transactions, Professor Xu has received international research prizes, such as the BCS/AT&T Brendan Murphy Prize and HiPEAC Transfer Award 2025, and led or co-led more than 20 research projects worth over £30M. He is also the co-founder of two university spinouts specializing in data analytics and AI software for optimizing data-centre performance, as well as in co-simulation and digital-twin technologies, and is the founding co-director of ACE3 AI Ltd.