AI and the Acceleration & Automation of Scientific Discovery
October 7, 2025
Online
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About the Session
The age of AI has moved beyond pattern recognition, to deep research and sophisticated reasoning models and agentic systems. These new--and rapidly improving!--capabilities present powerful possibilities for accelerating and even automating scientific discovery. But how do we connect powerful AI research and reasoning models to scientific experimentation and simulation? Dr. Ian Foster, a pioneer in high-performance computing, will discuss his vision for a "thought-action fabric"—a transformative framework designed to translate the hypotheses of AI models into tangible actions that expands our capabilities and shortens our timelines to breakthroughs.
Drawing from his recent work presented at the Trillion Parameter Consortium (TPC25) and other recent conferences, Dr. Foster will outline a blueprint for an AI-native discovery platform. This platform embeds a reasoning core within a dynamic ecosystem of data and knowledge repositories, first principles simulation models and AI surrogate models, and autonomous labs. He will explore how this fabric can empower AI agents to not just think, but to act: generating hypotheses, running experiments, evaluating outcomes, and learning from the results with full transparency. This talk will provide a look into a future where the scientific discovery process is accelerated and automated by AI, with human expert supervision--and ethics--remaining paramount for validation.
Speaker
Dr. Ian Foster
Director, Data Science and Learning Division, Argonne National Laboratory
Dr. Ian Foster is the Director of the Data Science and Learning Division, a Senior Scientist, and a Distinguished Fellow at Argonne National Laboratory. He is also the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago. A globally recognized leader in high-performance computing, Dr. Foster is known as one of the fathers of "grid computing," the precursor to today's cloud computing.
His work has been instrumental in enabling data-intensive, multi-institutional collaboration in fields ranging from high-energy physics to biomedicine. He is an elected Fellow of the American Association for the Advancement of Science (AAAS), the Association for Computing Machinery (ACM), and the British Computer Society (BCS). His numerous accolades include the ACM/IEEE Ken Kennedy Award and the British Computer Society's Lovelace Medal for his pioneering contributions to computer science.
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