Join us on August 20, 2025, for the CAE International Symposium on AI for Future Engineering!
The disruptive power of modern Artificial Intelligence is rapidly transforming every field of engineering, from design automation and predictive maintenance to intelligent control systems and sustainable infrastructure. As AI continues to evolve, it is redefining traditional engineering processes, enabling smarter decision-making, and opening new frontiers in innovation.
The 2025 CAE International Symposium on AI for Future Engineering will bring together leading researchers and practitioners to explore cutting-edge AI technologies and their transformative applications across diverse engineering disciplines.
This free, one-day online symposium, taking place on August 20, 2025, is open to everyone and will feature seminars and a panel discussion led by distinguished fellows from engineering and science academies around the world.
Program Co-Chairs: Jiangchuan Liu (Canada) and Dacheng Tao (Australia/Singapore)
(All times are in Eastern Daylight Time — EDT)
Opening
Break
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Conclusion
Kaoru Ota, Fellow of the Engineering Academy of Japan
Professor, Department of Sciences and Informatics, Muroran Institute of Technology, Japan
u.muroran-it.ac.jp/enes/~ota/
Title: Toward Human-Centered AI: Enhancing Wellbeing in Diverse Domains
Abstract
At the intersection of technology and society, human-centered AI is emerging as a powerful tool for enhancing quality of life. In this keynote, I will introduce engineering-driven AI applications across diverse domains — including UAV-based semantic communication for disaster response, RIS-assisted 6G networks for immersive user experiences, and AI-powered music transcription using synthesized data. Drawing from recent projects, the talk will highlight how AI can be optimized to serve real-world needs under resource constraints, adapt to user diversity, and support both critical infrastructure and creative expression. The goal is to share practical insights into building AI systems that are not only intelligent, but also aligned with human values and well-being.
Bio
Kaoru Ota received M.S. degree from Oklahoma State University, USA in 2008, B.S. and Ph.D. degrees from The University of Aizu, Japan in 2006, 2012, respectively. She is a Professor and MEXT Excellent Young Researcher with Muroran Institute of Technology (Muroran-IT), Japan. She is the director of the Center for Computer Science in Muroran-IT. She is Clarivate Analytics 2019, 2021, 2022 Highly Cited Researcher and is selected as JST-PRESTO researcher in 2021, Fellow of EAJ in 2022, and Fellow of AAIA in 2025.
Dacheng Tao, Fellow of the Australian Academy of Science
Distinguished University Professor and the Inaugural Director of the Generative AI Lab, College of Computing and Data Science, Nanyang Technological University, Singapore
dr.ntu.edu.sg/entities/person/Tao-Dacheng
Title: The Development Trend of AI
Abstract
Artificial Intelligence (AI) is advancing at an unprecedented pace, evolving from rule-based systems to today’s powerful generative models, and now toward autonomous, agent-based super intelligence with safety guarantee. This talk traces the waves of AI development, from early symbolic reasoning to the rise of perceptual and cognitive models, and explores how we are entering a new era of intelligent agents capable of interacting, planning, and adapting in complex environments.
Recent progress has followed a clear trajectory: first, scaling laws unlocked major breakthroughs during the training phase; then, focus shifted to inference, driving efficiency and reasoning under limited compute. Now, we are witnessing the rise of AI agents that operate with increasing autonomy, coordination, and decision-making capabilities.
But with great power comes great responsibility. As AI systems grow more capable, so do the risks: adversarial threats, backdoors, hallucinations, sycophancy, privacy violations, and social disruption. These vulnerabilities underscore the urgency of developing robust safeguards alongside powerful models.
The future of AI lies in achieving a careful balance, between innovation and regulation, capability and control. In this presentation, we explore how AI can be developed not just to serve human needs, but to evolve as a responsible partner in shaping our collective future.
Bio
Dacheng Tao is currently a Distinguished University Professor and the Inaugural Director of the Generative AI Lab in the College of Computing and Data Science at Nanyang Technological University. He was an Australian Laureate Fellow and the founding director of the Sydney AI Centre in the University of Sydney, the inaugural director of JD Explore Academy and senior vice president in JD.com, and the chief AI scientist in UBTECH Robotics. He mainly applies statistics and mathematics to artificial intelligence, and his research is detailed in one monograph and over 300 publications. His publications have been cited over 150K times and he has an h-index 180+ in Google Scholar. He received the 2015 and 2020 Australian Eureka Prize, the 2018 IEEE ICDM Research Contributions Award, 2020 research super star by The Australian, the 2019 Diploma of The Polish Neural Network Society, and the 2021 IEEE Computer Society McCluskey Technical Achievement Award. He is a Fellow of the Australian Academy of Science, ACM and IEEE.
Lin Cai, Fellow of The Canadian Academy of Engineering
Title: Engineering Tomorrow: Rising with AI Revolution
Abstract
The arc of industrial revolutions has consistently reshaped human civilization. This talk begins by drawing insights from history—examining the steam-powered first revolution, the electrically charged second, and the digitally-driven third. Each brought profound progress, but not without significant societal costs. As we enter the era of the Fourth Industrial Revolution—driven by artificial intelligence—we witness the convergence of the physical, digital, and biological realms, unlocking a new paradigm of human-machine synergy in decision-making. What can AI replace, and what remains uniquely human? We explore this boundary, highlighting opportunities for engineers not only to innovate the very infrastructure enabling AI but also to harness it in transformative applications—from intelligent sensing, communication, and computing to adaptive control systems. Through selected use cases, we illustrate the potential of AI to augment human capabilities rather than replace them. Ultimately, this revolution challenges us to learn from history and design a future where engineering and ethics, intelligence and empathy, innovation and inclusion evolve hand in hand.
Bio
Lin Cai is a Professor with the Department of Electrical & Computer Engineering at the University of Victoria. She is an Royal Society of Canada (RSC) Fellow, NSERC E.W.R. Steacie Memorial Fellow, Engineering Institute of Canada (EIC) Fellow, a Canadian Academy of Engineering (CAE) Fellow, and an IEEE Fellow. In 2020, she was elected as a 2020 “Star in Computer Networking and Communications” by N2Women. Her research interests span several areas in communications and networking, focusing on network protocol and architecture design supporting ubiquitous intelligence. She was a recipient of the NSERC Discovery Accelerator Supplement (DAS) Grants in 2010 and 2015, respectively, and the University of Victoria’s Silver Medal for Excellence in Research in 2023. She has co-founded and chaired the IEEE Victoria Section Vehicular Technology and Communications Joint Societies Chapter. She is an elected member of the IEEE Vehicular Technology Society (VTS) Board of Governors (BoG), 2019 – 2024 and serves its VP Mobile Radio since 2023. She has been a BoG member of IEEE Communications Society (2024-2026) and IEEE Women-in-Engineering (2022-2024). She is the Associate Editor-in-Chief for IEEE Transactions on Vehicular Technology and has served as a Distinguished Lecturer of both the IEEE VTS Society and the IEEE ComSoc Society.
Li Deng, Fellow of The Canadian Academy of Engineering
Chief AI Officer at a Quant Firm in New York City
Title: One simple equation that runs across neural speech recognition, computer vision, and quantitative finance
Abstract
Modern AI, built on deep neural networks, first took off with breakthroughs in speech recognition in 2009, then flourished in computer vision and in language processing by 2012-2015. Since 2017, it has entered—and disrupted—the field of quantitative finance. This talk offers a concise tour of this remarkable trajectory, drawing on the speaker’s own research to highlight pivotal moments in this applied neural network history. These milestones reveal a unifying principle that links deep learning’s most successful applications across speech recognition, computer vision, and quantitative finance.
Bio
Dr. Li Deng is a Fellow of the Canadian Academy of Engineering and a Life Fellow of the IEEE. He was a professor at the University of Waterloo and the Chief Scientist of AI at Microsoft in Seattle. He received the 2019 IEEE SPS Industry Leader Award “For leadership in pioneering research and development on large-scale deep learning that disrupted worldwide speech recognition industry and for leadership in natural language processing and financial engineering,” and 2015 IEEE SPS Technical Achievements Award for “Outstanding Contributions to Automatic Speech Recognition and to Deep Learning”. He currently serves as the Chief AI Officer at a quant firm headquartered in New York City.
Majid Bahrami, Fellow of The Canadian Academy of Engineering
Professor and Tier 1 Canada Research Chair in Alternative Energy Conversion Systems, Faculty of Applied Sciences, Simon Fraser University, British Columbia, Canada
www.sfu.ca/~mbahrami/
Title: What If AI Could Grow Food and Decarbonize Cities?
Abstract
AI’s rapid rise is driving unprecedented energy consumption and massive waste heat emissions. What if this heat could be turned into a climate asset rather than a liability? In this talk, I will explore how sorption-based thermal technologies can transform AI data center waste heat into cooling, heating, water, and CO₂ —resources that can decarbonize buildings and enable sustainable food production in greenhouses. This approach links digital growth to climate resilience and food security.
Bio
Dr. Bahrami is a Professor of Mechanical Engineering and Tier 1 Canada Research Chair in Alternative Energy Conversion Systems at SFU. He is a Fellow of the Canadian Academy of Engineers (FCAE) and the American Society of Mechanical Engineers (FASME). Bahrami championed interdisciplinary, collaborative research in multitudes of sustainable clean energy systems, including: harvesting and transforming low-grade heat for sustainable air conditioning, thermal energy storage, atmospheric water harvesting, heat pump systems and dehumidification for applications in automotive, agri-food, sustainable city, and hybrid thermal electric microgrids. He has a strong track record in successful collaboration with national and international research institutes and industry. He formed 2 start-ups; won national and international research and innovation awards; published 12 patents and 350 publications; and supervised 180+ highly qualified personnel, including 8 professors
Panelists:
Majid Bahrami, Lin Cai, Li Deng, Vincent Wong
Bio of Vincent Wong, Fellow of The Canadian Academy of Engineering
Professor, Department of Electrical and Computer Engineering, The University of British Columbia
people.ece.ubc.ca/~vincentw/Homepage/Home.html
Vincent Wong received his B.Sc. (with distinction) degree from the University of Manitoba in 1994, M.A.Sc. degree from the University of Waterloo in 1996, and Ph.D. from the University of British Columbia (UBC) in 2000, all in electrical engineering. From 2000 – 2001, he was a systems engineer at PMC-Sierra Inc. (now Microchip Technology Inc.). In 2002, he joined the Department of Electrical and Computer Engineering at the University of British Columbia, where he is currently a Professor. His research areas include wireless communication systems, mobile networking, Internet of things, smart grid, and energy systems. Dr. Wong is the Editor-in-Chief of the IEEE Transactions on Wireless Communications. He has served as an Area Editor of the IEEE Transactions on Communications and IEEE Open Journal of the Communications Society, an Associate Editor of the IEEE Transactions on Mobile Computing and IEEE Transactions on Vehicular Technology, and a guest editor of the IEEE Journal on Selected Areas in Communications, IEEE Wireless Communications, and IEEE Internet of Things Journal. He has served as a General Chair of the IEEE INFOCOM 2024. Dr. Wong is an IEEE Vehicular Technology Society Distinguished Lecturer (2023 – 2027) and was an IEEE Communications Society Distinguished Lecturer (2019 – 2020). He received the 2022 Best Paper Award from IEEE Transactions on Mobile Computing, and Best Paper Awards at the IEEE ICC 2022 and IEEE GLOBECOM 2020. He has served as the Chair of the IEEE Vancouver Joint Communications Chapter and the IEEE Communications Society Emerging Technical Subcommittee on Smart Grid Communications. Dr. Wong is a Fellow of the IEEE, Canadian Academy of Engineering, and the Engineering Institute of Canada.
