Speakers

Tongliang Liu is the Director of Sydney AI Centre (which has 11 academic staff and 100+ PhD students) and an Associate Professor in machine learning at The University of Sydney, Australia; a Visiting Scientist of RIKEN AIP, Tokyo, Japan; an Affiliated Professor with Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates; a Visiting Professor with University of Science and Technology of China, Hefei, China. He is also leading the Trustworthy Machine Learning Lab (TML Lab) at The University of Sydney, which hosts, attracts, and connects the best global talents to develop trustworthy machine learning techniques and tools, which are explainable, robust, fair, causally responsible, and privacy-preserving. Our mission is to make machines trustworthy, which is a foundation for our society to develop and deploy artificial intelligence to improve our lives. He was born in Yili, Xinjiang, China. He received his BEng degree from University of Science and Technology of China and PhD degree from University of Technology Sydney (UTS). Upon graduation, he got a Lecturer position at UTS. He then joined The University of Sydney in 2017 as a Lecturer. He has published more than 200 papers at leading ML/AI conferences and journals. According to CS Rankings, he has been ranked as the first in machine learning in Australasia. He received the Young Distinguished Scientist Award from the International Association of Engineers (IAENG) in 2025; the Outstanding Research Contribution Award from the Computing Research and Education Association of Australasia (CORE) in 2024; Eureka Prize shortlist for Emerging Leader in Science from Australian Museum in 2023; IEEE AI's 10 to Watch Award from the IEEE Computer Society in 2022; Future Fellowship Award from Australian Research Council (ARC) in 2022; Faculty Early Career Research Excellence Award at The University of Sydney in 2021; Top-40 Early Achievers by The Australian in 2020; and Discovery Early Career Researcher Award (DECRA) from ARC in 2018. Tongliang is also very proud of his talented students, who have made/are making/will make significant contributions to advancing science. They have also been recognised by many awards, e.g., Google PhD Fellowship Awards. He is a Co-Editor-in-Chief of Neural Networks. He is regularly the Senior Area Chair of NeurIPS and ICLR, the Area Chair of ICML, NeurIPS, ICLR, UAI, IJCAI, and AAAI. He is an Associate Editor of IEEE TPAMI, JAIR, TMLR, MLJ, TIP, and ACM Computing Surveys, and on the Editorial Board of Journal of Machine Learning Research.