*More details will be added to the schedule as they become available.*
For a complete list of conference talk titles and abstracts, click here.
For a complete list of conference poster titles and abstracts, click here.
Schedule for Tuesday, September 2
| Time (CT) | Session | Location |
|---|---|---|
| 8:00–9:30 a.m. | Breakfast and registration (for tutorial participants and volunteers) | Reception/lobby |
| 9:30–10:30 a.m. | Tutorials—“Scientific AI at Scale: Architectures and Distributed Training”—AI for science is accelerating as a data-and-model revolution takes hold, with advances in deep learning and foundation models showing that scale unlocks discovery, while translating those gains into scientific value still requires domain-specific design and customization. This tutorial will survey the major modeling architectures and learning approaches used for scientific datasets and tasks, and cover scalable training strategies, including data, model, and pipeline parallelism and distributed I/O, enabling efficient training on leadership-class systems at Argonne’s ALCF. | |
| 10:30–11:00 a.m. | Coffee break & poster set up | |
| 11:00 a.m.–12:00 p.m. | Tutorials—“Scientific AI at Scale: Architectures and Distributed Training” (cont.) | |
| 12:00–1:00 p.m. | Lunch (for tutorial participants) | |
| 1:00–1:30 p.m. | Opening | Auditorium and Zoom |
| 1:30–2:30 p.m. | Plenary 1 • Federica Bianco, University of Delaware—TBD | Auditorium and Zoom |
| 2:30–3:00 p.m. | Poster lightning talks | Auditorium and Zoom |
| 3:00–4:00 p.m. | Coffee break @ posters | SkAI Hub area |
| 4:00–5:20 p.m. | Inference and uncertainty quantification for large and complex data 1 • Ved Shah, Northwestern University—“ORACLE: A Real-Time, Hierarchical, Deep-Learning Photometric Classifier for the LSST” • Hyosun Park, Yonsei University—“Transformer-based Reduction of PSF Effect and Correlated Noise for Precision Dark Matter Mapping” • Georgios Valogiannis, The University of Chicago—“Saturating Cosmological Information with AI: Field-Level Inference and Beyond” • Shubhendu Trivedi, Fermilab—“Conformal Hierarchical Simulation-based Inference with Local Validity” • Patricia Iglesias-Navarro, Institute of Astrophysics of the Canary Islands—“Simulation-based inference of galaxy properties from JWST pixels” | Auditorium and Zoom |
| 5:20–5:30 p.m. | Day 1 wrap-up: Introduction to Discovery Engine crowdsourcing ideas, glossary, community norms | Auditorium and Zoom |
The SkAI Institute is one of the National Artificial Intelligence Research Institutes funded by the U.S. National Science Foundation and Simons Foundation. Information on National AI Institutes is available at aiinstitutes.org.
