Professor YANG Qiang

Chief Artificial Intelligence Officer
Director, PolyU Academy for Artificial Intelligence
Chair Professor of Artificial Intelligence

Fellow of Royal Society of Canada
Fellow of Canadian Academy of Engineering
Fellow of Association for the Advancement of Artificial Intelligence
Fellow of American Association for the Advancement of Science
Fellow of International Association of Pattern Recognition
Fellow of Institute of Electrical and Electronics Engineers
Fellow of Association of Computing Machinery
Fellow of Chinese Association of Artificial Intelligence

Full academic bio

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Professor YANG Qiang received his BSc. degree in Astrophysics from Peking University and his PhD degree from the Department of Computer Science at University of Maryland, College Park, in 1989. He was a faculty member in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology between 2001 and 2023, in which he was a Chair Professor (2015 -2023) and former head of the CSE department (2015 – 2018). Professor and NSERC Industry Chair at Simon Fraser University and Associate Professor at the University of Waterloo in Canada between 1989 and 2001.

Professor Yang’s research interests lie in artificial intelligence, machine learning, federated learning, transfer learning, case-based reasoning and AI planning, and he is a world-leading pioneer in the research and application of federated learning, transfer learning and AI planning. In federated learning, he and his colleagues have developed novel algorithms for distributed and privacy-preserving machine learning, led the development of the first international standard on federated learning, launched the first open-source software platform on federated learning and developed many successful federated learning applications in, for example, finance, medicine and online commerce. In transfer learning, he and his students have developed novel algorithms for transfer learning under complex constraints and applied the algorithms to many challenging real-world problems. In AI planning, he and his students have developed the theory and one of the first open-source software applications for hierarchical automated planning.

I take pride in mentoring the next generation of AI researchers, many of whom have become influential figures in academia and industry, advancing my vision of responsible, impactful AI.

Professor Yang Qiang

Professor Yang is a fellow of the Canadian Academy of Engineering and Royal Society of Canada, as well as of the Institute of Electrical and Electronics Engineers (IEEE), Association of Computing Machinery (ACM), Association for the Advancement of Artificial Intelligence (AAAI), American Association for the Advancement of Science (AAAS), International Association of Pattern Recognition (IAPR) and Chinese Association of Artificial Intelligence (CAAI). He was President of the International Joint Conference on Artificial Intelligence between 2019 and 2021 and President of the Hong Kong Society of Artificial Intelligence and Robotics. He received the ACM SIGKDD Distinguished Service Award, the Department of Computer Science Alumni Hall of Fame at the University of Maryland in 2017, and the IJCAI Distinguished Service Award in 2023.

YANG Qiang_Quote_pic

Professor Yang has been active in serving the community. He was the Conference and Programme Chairs for the ACM KDD Conference, Programme Chair for the IJCAI Conference and Conference Chair for the AAAI Conference. He served as President of the IJCAI board of trustees from 2017 to 2019. He was also the Founding Editor-in-Chief of ACM Transactions on Intelligent Systems and Technology and the Founding Editor-in-Chief of IEEE Transactions on Big Data. Besides his academic research.

Professor Yang is also active in industrial practice. He was the Founding Director of the Huawei Noah’s Ark Lab, former Chief Technology Advisor at WeChat (2015-2018), Co-founder of 4th Paradigm Technology Ltd and Chief AI Officer of WeBank between 2018 and 2025.

Professor Yang has authored or co-authored more than ten books in AI, including books on transfer learning, planning and federated learning. He holds over 220 patents in AI.

Research Interests

Artificial Intelligence

Machine Learning

Federated Learning

Transfer Learning

Case-based Reasoning and AI Planning

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Professor YANG Qiang

Research Interests