Prof. Baochun Li

Baochun Li received his B.Engr. degree from the Department of Computer Science and Technology, Tsinghua University, China, in 1995 and his M.S. and Ph.D. degrees from the Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, in 1997 and 2000. Since 2000, he has been with the Department of Electrical and Computer Engineering at the University of Toronto, where he is currently a Professor. He holds the Bell Canada Endowed Chair in Computer Engineering since August 2005. His current research interests include cloud computing, security and privacy, distributed machine learning, federated learning, and networking.

Dr. Li has co-authored more than 500 research papers, with a total of over 29000 citations, an H-index of 90 and an i10-index of 367, according to Google Scholar Citations. He was the recipient of the IEEE Communications Society Leonard G. Abraham Award in the Field of Communications Systems in 2000, the Multimedia Communications Best Paper Award from the IEEE Communications Society in 2009, the University of Toronto McLean Award in 2009, the Best Paper Award from IEEE INFOCOM in 2023, and the IEEE INFOCOM Achievement Award in 2024. He is a Fellow of the Canadian Academy of Engineering, a Fellow of the Engineering Institute of Canada, and a Fellow of IEEE.

In March 2026, Andrej Kaparthy predicted our future: "Research is now entirely the domain of autonomous swarms of AI agents running across compute cluster megastructures in the skies." While this sounds like science fiction, I argue that it may arrive before we know it (well, sans the "in the skies" part). At the very least, I believe that the "swarm of AI agents" can help accelerate the pace of academic research substantially, and in particular reproducible research with clearly defined benchmarks. In this talk, I will share with you why I think this is the case. Using both slide narratives and live demos, I will introduce how I drive a swarm of AI agents to effectively accelerate my recent research on Days, a discrete-event network simulator written in Rust. With such a swarm of AI agents, our imagination — rather than time or execution — becomes the limit when it comes to academic research.

Professor Sarah Irene Brutton Kenderdine

Professor Sarah Kenderdine researches at the forefront of interactive and immersive experiences for galleries, libraries, archives and museums. She is professor at the École Polytechnique fédérale de Lausanne (EPFL), Switzerland, leading the Laboratory for Experimental Museology (eM+) and is curator-at-large of EPFL Pavilions. Sarah has pioneered the framework of computational museology, a scaffold that unites machine intelligence with data curation, ontology with visualization, and communities of publics and practitioners with embodied participation through kinaesthetic and interactive interfaces. She has created over 110 exhibitions and major installations. Her upcoming book, together with Lily Hibberd, is Deep Fakes: A Critical Lexicon of Digital Museology will be published by Routledge on 17 November 2025 (OA).

This project explores how artificial intelligence (AI) is transforming museums into anticipatory systems mediating between cultural heritage, science, and speculative futures. It distinguishes between discriminative and generative AI as complementary forms of cultural computation. Discriminative AI analyzes vast repositories of cultural data revealing hidden relationships and generating new interpretive frameworks. The Narratives from the Long Tail project exemplifies this approach, using machine learning to create narrative coherence across more than 200,000 hours of archival video. Generative AI, by contrast, produces new cultural forms that invite visitors to co-create within algorithmically mediated worlds. Projects such as the Geneva Public Portal to Anticipation engage global publics in exploring emerging science and speculative futures. Together, these modalities reposition the museum as both archive and laboratory for cultural foresight.

Acknowledgement: This Distinguished Lecture is supported under Daniel and Kitty Tse Visiting Professorship Scheme.

Prof. John C. S. LUI

John C.S. Lui is currently the Choh-Ming Li Chair Professor at the Chinese University of Hong Kong. His current research interests are in quantum Internet and the theory of online learning and optimization. He has been a visiting professor at UCLA, Columbia University, Caltech, Uni. of Maryland, Purdue University, Univ. of Massachusetts at Amherst, INRIA (France) and NII (Japan). He has been serving as the senior editor and associate editor in various IEEE and ACM Transactions, and has received numerous best paper awards in IEEE/ACM conferences, as well as teaching awards from CUHK. His personal interests include films and general readings.

In this talk, I will first give a brief introduction to quantum computing, and highlight the importance and opportunities for us to consider fundamental research in quantum Internet, in particular, how quantum network can enable quantum information transmission, quantum parallel processing and quantum distributed processing. I will then give a brief introduction about online learning theory, and how it can enable to explore interesting problems in building quantum network/internet. In particular, I will discuss the quantum path selection problem, as well as quantum boarder gateway protocol (QBGP).