Information about the conference speakers will be available after 1 September, once the program has been finalised. Please check back for updates as we confirm an exciting lineup of experts and thought leaders. In the meantime, we invite interested researchers to submit abstracts via our Call for Abstracts online form
International keynote speaker
We are delighted to announce that Bin Yu will attend and present as an international keynote speaker. Bin Yu is CDSS Chancellor’s Distinguished Professor in Statistics, EECS, and Center for Computational Biology, and Scientific Advisor at the Simons Institute for the Theory of Computing, all at UC Berkeley. Her research focuses on the practice and theory of statistical machine learning, veridical data science, responsible and safe AI, and solving interdisciplinary data problems in neuroscience, genomics, and precision medicine. She and her team have developed algorithms such as iterative random forests (iRF), stability-driven NMF, and adaptive wavelet distillation (AWD) from deep learning models. She is a member of the National Academy of Sciences and of the American Academy of Arts and Sciences. She was a Guggenheim Fellow, IMS President, and delivered the IMS Rietz and Wald Lectures and Distinguished Achievement Award and Lecture (formerly Fisher Lecture) of COPSS. She holds an Honorary Doctorate from The University of Lausanne.
Invited speakers
Professor Karin Verspoor FTSE FAIDH is Executive Dean of the School of Computing Technologies at RMIT University in Melbourne, Australia. She is passionate about using artificial intelligence to enable biological discovery and clinical decision support from data, with a specific emphasis on the use of natural language processing to transform unstructured data in biomedicine into actionable information.
Yuan-Fang Li is the Chief AI Scientist at Oracle Health and AI in Australia, where he works closely with a team of over 60 applied scientists to develop cutting-edge AI solutions for electronic health records (EHR) systems, aimed at transforming healthcare. In this role, Yuan-Fang provides strategic scientific leadership, ensuring the delivery of impactful, high-quality and innovative AI-driven products. Yuan-Fang’s research interests include large language models, knowledge graphs, multimodal learning, and neuro-symbolic AI. He is also an Associate Professor in the Faculty of Information Technology at Monash University. Yuan-Fang’s work bridges academic innovation and real-world impact, advancing the frontiers of AI in both industry and academia.