Join us for an in-person Distinguished Speaker event featuring Guillaume Fontaine, Director of the McGill RISE³ Implementation Science Lab and Assistant Professor at McGill University. An internationally recognized leader in implementation science, Fontaine's research advances the use of evidence-based frameworks and methodologies to improve healthcare outcomes, with a particular focus on integrating artificial intelligence into implementation research and practice.

Title: The Implementation Problem in AI: Perspectives from Implementation Science

Abstract: AI systems can perform well in testing and still deliver limited benefits in practice. Their impact depends on whether people adopt them, how they fit into everyday work, and whether their use produces lasting benefits across populations.

This talk examines how AI and implementation science can inform each other. Implementation science studies how evidence and innovations are adopted, integrated into routine practice, and sustained. It offers methods to identify barriers to AI use, test strategies to address those barriers, and assess outcomes beyond technical performance. AI also raises questions for the field. As AI systems are updated and used in different settings, what should remain consistent in our approach to implementation, what needs to be adapted, and how can effective use be sustained?

In the other direction, AI is being explored as a tool to support implementation research. Applications include reviewing evidence, identifying barriers to change, developing implementation strategies, and supporting evaluation. I will discuss how to assess the reliability of these contributions, whose knowledge and perspectives they reflect, and where local knowledge and human judgment remain essential.

I will argue that realizing AI’s promise requires asking what works, for whom, under what conditions, and how to achieve lasting, equitable benefits at scale.

Dr. Guillaume Fontaine (PhD, MSc, RN) is the Director of the McGill RISE³ Implementation Science Lab and an Assistant Professor at McGill University in Montreal, Canada. He is a Principal Investigator in the Centre for Clinical Epidemiology at the Lady Davis Institute, and holds visiting appointments in the Viral Hepatitis Clinical Research Program at the Kirby Institute, UNSW Sydney, and the Centre for Implementation Research, Ottawa Hospital Research Institute. He co-leads the Implementation Science Research Pillar for the Canadian Network on Hepatitis C, co-leads the Methods Think Tank for the Pan-Canadian HIV/AIDS Clinical Trials Research Network, serves on the Steering Committee of Knowledge Translation Canada, and co-chairs the Global Network on Implementation and Data Sciences. His research program focuses on applying and advancing implementation science frameworks and methodologies to improve healthcare outcomes, , with particular emphasis on the integration of AI into implementation research and practice.

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Regular registration for Winter quarter begins

Join us for an in-person Distinguished Speaker event featuring Frankie Liu, Senior Product Manager in Omniverse Content and Simulation at NVIDIA. Drawing on more than two decades in visual effects, Liu will explore the parallels between the digital transformation of filmmaking and today’s rise of physical AI, examining how NVIDIA Omniverse, digital twins, and simulation are helping researchers and engineers build virtual worlds where intelligent machines can learn, test, and interact.

Please note: this is an IN-PERSON event only! There will not be a recording.

Title: The Worlds We Build: AI, NVIDIA Omniverse, and the Rise of Physical AI

Abstract: The rise of digital filmmaking transformed how artists built worlds and told stories. Drawing on my twenty years in visual effects, I’ll reflect on that transition and explore another transformation now unfolding through AI, with implications reaching far beyond the screen.

Through NVIDIA Omniverse and examples from industry and robotics, I’ll explore how the digital worlds we build can help us understand physical systems, test new ideas, and give intelligent machines places to learn. I’ll discuss digital twins and what they make possible:
- Exploring a factory before it is built
- Testing how robots interact with their surroundings
- Studying situations that would be difficult or costly to reproduce in the real world

Along the way, I’ll explain why the foundations of these environments, including shared 3D data, materials, physics, and sensor simulation, matter to the questions we want to answer.

I’ll then connect these capabilities to the rise of physical AI: systems that perceive, reason, and act in physical environments. We’ll explore how real-world observations inform simulation, how AI helps create new experiences for training and testing, and how evaluation guides the next round of development. This “data flywheel” connects the worlds we build with the machines learning to operate within them.

Drawing connections between filmmaking and simulation, I’ll offer a personal perspective on this transition and the opportunities it creates for engineering, research, and creative problem-solving.

Frankie Liu is a Senior Product Manager in Omniverse Content and Simulation at NVIDIA. He joined NVIDIA in 2019 as a Product Manager overseeing physically based materials and rendering for Omniverse. He later transitioned to Omniverse Customer Success before moving into Content and Simulation.

He received his bachelor’s degree in computer engineering from Northwestern University in 1997 and brings over twenty years of experience in visual effects. His career includes serving as Head of Lighting at Weta Digital in New Zealand and North America, Senior Research and Development and Rendering Engineer at DreamWorks Animation, and Senior Computer Graphics Supervisor at Sony Pictures Imageworks and Digital Domain. His film and television work includes Titanic, Harry Potter and the Sorcerer’s Stone, How to Train Your Dragon 2, Avatar: The Way of Water, Avengers: Endgame, and Game of Thrones.

He is a member of the Visual Effects Society and the Academy Software Foundation, and serves as a voting member of the MaterialX Technical Steering Committee.

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Dissertation, PhD Final Exam, and change of grade forms due to TGS for Fall PhD candidates

Thanksgiving Vacation begins at 6:00 PM (No classes, University offices closed)

Fall Classes Resume

Fall classes end

Fall Exams begin

Fall exams end