ACML 2024 Distinguished Speakers Series: Professor Dinh Phung
ACML 2024 Distinguished Speakers Series: Professor Dinh Phung
Dinh Phung is a Professor and Head, Department of Data Science and AI, Monash University, Australia – where it hosts approximately 50 staff and 150 PhD students dedicated fully to advancing the frontiers of AI research and education. His research interests broadly cover machine learning and artificial intelligence, including the young field of optimal transport mathematics theory in deep learning, trustworthy AI and graphical models.
He has won numerous best research awards, published several technical papers and attracted research substantial fundings in these areas. He was the Finalist for the prestigious Australian Museum Eureka Prize for Excellence in Data Science in 2020 and the current Editor-In-Chief for the living edition of the Encyclopedia in Machine Learning and Data Science.
Prof. Dinh Phung
Monash University
He will discuss the problem of distribution matching as an emerging approach to several learning tasks. This includes the discussion of statistical divergences and their desirable properties and limitations, which leads to his motivation to optimal transport and Wasserstein distance. A brief historical development will be introduced with an emphasis on their properties and possible uses for diverse machine learning tasks. He will then conclude with discussing how they can be specifically utilised to solve important tasks in the domains such as robust machine learning, generative modelling, domain transfer and graphical models.