Technical Sharing Session with National Research Foundation

Marta Kwiatkowska is a Professor of Computing Systems and Fellow at Trinity College, University of Oxford. Her area of expertise lies in probabilistic and quantitative verification techniques and the synthesis of correct-by-construction systems from quantitative specifications.

She led the development of the probabilistic model checker PRISM, winner of the 2024 ETAPS Test-of-Time Tool Award, which has been used to model and verify numerous case studies across a variety of application domains. Recently, she has been focusing on safety and trust in Artificial Intelligence, with an emphasis on safety and robustness guarantees for machine learning.

Marta has been the recipient of two ERC Advanced Grants and an honorary doctorate from KTH Institute of Technology, and was the first female winner of the Royal Society Milner Medal. She is a Fellow of the ACM, a Member of Academia Europea, and a Fellow of the Royal Society.

Peter Bartlett is Professor of Statistics and Computer Science at UC Berkeley and Principal Scientist at Google DeepMind. At Berkeley, he is the Machine Learning Research Director at the Simons Institute for the Theory of Computing, Director of the Foundations of Data Science Institute, and Director of the Collaboration on the Theoretical Foundations of Deep Learning, and he has served as Associate Director of the Simons Institute.

He is President of the Association for Computational Learning, Honorary Professor of Mathematical Sciences at the Australian National University, and co-author with Martin Anthony of the book Neural Network Learning: Theoretical Foundations.

He was awarded the Malcolm McIntosh Prize for Physical Scientist of the Year in Australia in 2001, was chosen as an Institute of Mathematical Statistics Medallion Lecturer in 2008, an IMS Fellow and Australian Laureate Fellow in 2011, a Fellow of the ACM in 2018, and recipient of the Chancellor's Distinguished Service Award in 2023. He was elected to the Australian Academy of Science in 2015.

Jun Sun is a Professor at Singapore Management University (SMU). He earned his Bachelor’s and Ph.D. degrees in Computer Science from the National University of Singapore (NUS) in 2002 and 2006, respectively, and has been a faculty member since 2010.

His research interests span AI safety, software engineering, formal methods, and more. He is passionate about designing algorithms to solve challenging real-world problems and is equally devoted to enjoying life.

Sun has published over 300 journal articles and conference papers. His work has been recognized with ACM Distinguished Paper Awards multiple times.

Dr. Raymond Chan is an experienced AI specialist with a deep understanding of machine learning algorithms, who has successfully developed and implemented innovative solutions for a range of industries.

Holding a doctorate in Computer Science, Dr. Chan has gained extensive experience working with large (petabyte) datasets and developing predictive models in both Fortune 500 companies and leading start-ups. He has consistently been recognised for his contributions to academia with several publications in leading academic journals.

Dr. Chan has designed innovative AI technologies that have been widely adopted within businesses. As an AI specialist, he is passionate about leveraging cutting-edge technologies to solve complex business problems and drive innovation.