Speaker: Dr. Ian Foster
Time: 09:05 AM - 10:00 AM
Session Type: Featured Speaker
Trillion-parameter, science-tuned foundation models can speed discovery, but only inside an AI-native Scientific Discovery Platform (SDP) that connects models to tools, data, HPC, and robotics. I argue for community co-development of the SDP, via open interfaces, shared schedulers, knowledge substrates, provenance, and evaluation, alongside shared models. Early results suggest that such a co-designed stack can boost throughput and reliability in materials and bio workflows, enabling human–AI teams to turn knowledge into experiments and experiments into insight.
Dr. Ian Foster is the Director of Argonne’s Data Science and Learning Division, Argonne Senior Scientist and Distinguished Fellow and the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago. He was the Director of Argonne’s Computation Institute from 2006 to 2016. Foster’s research contributions span high-performance computing, distributed systems, and data-driven discovery. He has published hundreds of scientific papers and eight books on these and other topics. Methods and software developed under his leadership underpin many large national and international cyberinfrastructures. Foster received a BSc (Hons I) degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science. His awards include the Global Information Infrastructure (GII) Next Generation award, the British Computer Society’s Lovelace Medal, R&D Magazine’s Innovator of the Year, the IEEE Tsutomu Kanai award, and honorary doctorates from the University of Canterbury, New Zealand and CINVESTAV, Mexico. He is an elected Fellow of the American Association for the Advancement of Science, the Association for Computing Machinery, and British Computer Society.