Keynote Speakers

Ryan D’Arcy

Ryan D’Arcy

Simon Fraser University

Dr. Ryan C.N. D’Arcy is a Canadian innovator in neuroscience, neurotechnology, and medical imaging. He co-founded HealthTech Connex and the Health and Technology District. Dr. D’Arcy also holds a BC Leadership Chair in Medical Technology, is a full Professor at Simon Fraser University, and a member of the DM Centre for Brain Health at the University of British Columbia. He has published more than 275 academic works, attracted more than $100 Million in competitive research and innovation funding, and been recognized through numerous awards and distinctions. Dr. D'Arcy is a 3X TEDx speaker, who speaks frequently on brain health innovations around the world. Dr. D’Arcy received a B.Sc. (with distinction) from the University of Victoria along with both M.Sc. and Ph.D. degrees in neuroscience from Dalhousie University (Killam Scholar). He completed post-doctoral training in medical imaging physics at the National Research Council’s Institute for Biodiagnostics, and holds a professional engineering designation in Neurotechnology (PlEng). He spent over a decade leading the development of Atlantic Canada’s biomedical imaging cluster before returning home to BC to catalyze and lead large scale health technology initiatives aimed at positively impacting billions of brains.

Keynote Title: Technologies disrupting brain health

Abstract: From the emergence of vital signs for cognition to pushing the limits through neuroplasticity - brains can be changed for the better. In spite of unprecedented advances in neurotechnology and neuroimaging, the gap in available brain health care remains relatively unchanged for decades. Put another way, the questions: "How is my brain health?" and "What can I do to improve my brain health?" are still among the most challenging questions to ask any healthcare provider. This talk will demonstrate real-world future technology successes and solutions that have bridged this gap to unleash the brain's potential to recover and optimize at any time.

Yingxu Wang

Bethany Edmunds

Northeastern University

Dr. Bethany Edmunds is recognized leader in Computer Science and STEM education within North America. She holds a Ph.D. in Computer Science from Rutgers University where she researched Reinforcement Learning and is currently Director of Computing Programs, Associate Director of Network Programs, and Teaching Professor at Northeastern University’s Vancouver campus. Bethany is passionate about breaking down barriers to create greater diversity, access, and inclusivity within the technology community. She brings together expertise in software development, machine learning, and educational innovation to create STEM opportunities for people of all backgrounds and abilities. Dr. Edmunds has been named one of BC Business's Most Influential Women in STEM, Business in Vancouver's Forty under 40, and YWCA’s Women of Distinction and currently serves on the Board of Directors of the Artificial Intelligence Network of British Columbia and as President of Women in Machine Learning.

Yingxu Wang

Cristina Conati

University of British Columbia

Dr. Conati is a Professor of Computer Science at the University of British Columbia, Vancouver, Canada. She received a M.Sc. in Computer Science at the University of Milan, as well as a M.Sc. and Ph.D. in Intelligent Systems at the University of Pittsburgh. Conati’s research is at the intersection of Artificial Intelligence (AI), Human Computer Interaction (HCI) and Cognitive Science, with the goal to create intelligent interactive systems that can capture relevant user’s properties (states, skills, needs) and personalize the interaction accordingly. Conati has over 100 peer-reviewed publications in this field and her research has received awards from a variety of venues, including UMUAI, the Journal of User Modeling and User Adapted Interaction (2002), the ACM International Conference on Intelligent User Interfaces (IUI 2007), the International Conference of User Modeling, Adaptation and Personalization (UMAP 2013, 2014), TiiS, ACM Transactions on Intelligent Interactive Systems (2014), and the International Conference on Intelligent Virtual Agents (IVA 2016). Dr. Conati is an associate editor for UMUAI, ACM TiiS, IEEE Transactions on Affective Computing, and the Journal of Artificial Intelligence in Education. She served as President of AAAC, (Association for the Advancement of Affective Computing), as well as Program or Conference Chair for several international conferences including UMAP, ACM IUI, and AI in Education. She serves on the Executive Committees of AAAI (Association for the Advancement of Artificial Intelligence) and of CAIDA (the UBC Center for Artificial Intelligence, Decision AMking and Action)

Yingxu Wang

Yingxu Wang

University of Calgary

Dr. Yingxu Wang is professor of cognitive systems, brain science, software science, and intelligent mathematics. He is the founding President of International Institute of Cognitive Informatics and Cognitive Computing (I2CICC). He is FIEEE, FBCS, FI2CICC, FAAIA, FWIF, and P.Eng. He has held visiting professor positions at Univ. of Oxford (1995, 2018-2022), Stanford Univ. (2008, 2016), UC Berkeley (2008), MIT (2012), and a distinguished visiting professor at Tsinghua Univ. (2019-2022). He received a PhD in Computer Science from the Nottingham Trent University, UK, in 1998 and has been a full professor since 1994. He is the founder and steering committee chair of IEEE Int’l Conference Series on Cognitive Informatics and Cognitive Computing (ICCI*CC) since 2002. He is founding Editor-in-Chiefs and Associate Editors of 10+ Int’l Journals and IEEE Transactions. He is Chair of IEEE SMCS TC-BCS on Brain-inspired Cognitive Systems, and Co-Chair of IEEE CS TC-CLS on Computational Life Science. His basic research has spanned across contemporary scientific disciplines of intelligence, mathematics, knowledge, robotics, computer, information, brain, cognition, software, data, systems, cybernetics, neurology, and linguistics. He has published 600+ peer reviewed papers and 38 books/proceedings. He has presented 65 invited keynote speeches in international conferences. He has served as honorary, general, and program chairs for 40 international conferences. He has led 10+ international, European, and Canadian research projects as PI. He is recognized by Google Scholar as world top 1 in Software Science, top 1 in Cognitive Robots, top 8 in Autonomous Systems, top 2 in Cognitive Computing, and top 1 in Knowledge Science with an h-index 62. He is recognized by ResearchGate as among the world’s top 1% scholars in general and in several contemporary fields encompassing artificial intelligence, autonomous systems, theoretical computer science, engineering mathematics, software engineering, cognitive science, information science, and computational linguistics, etc.

Keynote Title: From Data-Aggregative Learning to Cognitive Knowledge Learning Enabled by Autonomous AI Theories and Intelligent Mathematics

Abstract: This keynote lecture presents a fundamental AI theory and the HMML framework for the design and implementation of Autonomous Machine Learning (AML). It is discovered that the basic unit of knowledge for AML is a binary relation (bir) [28,46], which is no longer a bit as that of data at low-level learning. It is recognized that no classic AI machine could achieve the level of AML by traditional data-aggregation neural network technologies, because high-level intelligence, encompassing inductive knowledge acquisition, causal reasoning, and robust decision-making, is cognitively independent from data and their magnitude. Therefore, the emerging technology of advanced AML for knowledge acquisition will trigger unprecedented AAI technologies beyond current level of data-driven AI systems according to the HMML theory