Seminar by Prof. Yupeng LI (HKBU) on 14 May 2024

Title: Toward a Trustworthy Digital Future: Robust Online Machine Learning and Intelligent Fact-Checking 

Time: 14 May 2024, Tuesday, 4pm-5pm

Venue: LT9 (NS4-04-39)

Abstract:

Online machine learning is a computing paradigm where agents cooperate to predict online data samples in a centralized or decentralized AI system. Despite its competitive capability in handling large-scale online data, it is yet to be widely adopted in real-world applications due to the challenges in robustness in the presence of endogenous and exogenous threats. This talk will address the trustworthiness of such AI systems and introduce our recent efforts in threat-resilient (de)centralized online learning mechanisms. The trustworthiness concerns lie in the information that the AI systems interact with as well. Our world is increasingly suffering from the unrestrained spread of misinformation in many areas.  Intelligent fact-checking has become more important in the era of Generative AI. This talk will also introduce our research in combating misinformation. We will address the robustness of rumor detection techniques as well as a carefully constructed benchmarking dataset for fake news detection. The dissemination of misinformation has propelled fact-checking to the forefront of academic research and societal concerns. Aiming at building a trustworthy digital future, we believe our research can help make our world a better one.

Bio:

Yupeng Li received his PhD degree in computer science at The University of Hong Kong. He was a postdoctoral research fellow at the University of Toronto. He is an assistant professor at the Department of Interactive Media at Hong Kong Baptist University (HKBU). He is also a Director of a Master's program and has been Associate Director (Research and Technology) of HKBU Fact Check Center. He is interested in studying trustworthy machine learning in networking and social computing. He is excited about interdisciplinary research that applies robust algorithmic techniques to edging problems. Dr. Li takes advantage of powerful techniques of learning, algorithms, and game theory to design and analyze networked systems, such as information and social networks. His works have been accepted in venues such as MobiHoc, The ACM Web Conference, INFOCOM, ICDCS, JSAC, ToN, TMC, and ICA. Dr. Li has been awarded the distinction of Distinguished TPC Member of the IEEE INFOCOM 2022 and 2024 and the Rising Star in Social Computing Award by CAAI. He serves on several technical committees of top conferences in computing-related areas. He was the TPC Co-Chairs for an ICDCS Track in 2024 and SocialMeta 2023.