*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 Wednesday, September 3
| Time (CT) | Session | Location |
|---|---|---|
| 8:00–9:00 a.m. | Breakfast and registration | Kitchen-dining area |
| 9:00–10:00 a.m. | Plenary 2—Session chair: Aggelos Katsaggelos, Northwestern University • George Karniadakis, Brown University—“From Physics-Informed Machine Learning to Physics-Informed Machine Intelligence: Quo Vadimus?” | Auditorium and Zoom |
| 10:00–10:30 a.m. | Coffee break @ posters | SkAI Hub area |
| 10:30 a.m.–12:00 p.m. | Physics-informed architectures, interpretability, and ethics 1—Session chair: Lu Cheng, University of Illinois Chicago • Invited speaker: Chenhao Tan, The University of Chicago—“Structured Creativity in Science: AI for Hypothesis Generation and Research Ideation” • Manuel Ballester Matito, Northwestern University—“Accelerating Stellar Structure Modeling with Neural PDE Solvers” • Matt Ho, Columbia University—“Learning the Universe: Building a Scalable, Verifiable Emulation Pipeline for Astronomical Survey Science” • Laura Trouille, Adler Planetarium, Zooniverse—“Zooniverse and SkAI: Human-AI Collaboration for Scalable Scientific Discovery” | Auditorium and Zoom |
| 12:00–1:30 p.m. | Lunch/mentoring time | Kitchen-dining area |
| 1:30–2:50 p.m. | Generative AI for scientific data analysis and simulations 1—Session chair: Sandeep Madireddy, Argonne National Laboratory • Jiezhong Wu, Northwestern University—“A foundation AI model to infer the physics of transients” • Shunyuan Mao, Rice University—“Multi-resolution neural representation for self-supervised image reconstruction in radio interferometry” • Bin Xia, Georgia Tech and Argonne National Laboratory—“Towards a Generalizable Multi-Modal Foundation Model for Astrophysical Data” • Supranta Boruah, University of Pennsylvania—“Generative machine learning solutions for weak lensing mass mapping” • Tianao Li, Northwestern University—“Probabilistic Imaging of Galaxies for Weak Gravitational Lensing” | Auditorium and Zoom |
| 2:50–3:15 p.m. | Coffee break @ posters | SkAI Hub area |
| 3:15–4:15 p.m. | Poster session 1 | SkAI Hub area |
| 4:15–5:15 p.m. | Inference and uncertainty quantification for large and complex data 2—Session chair: Chihway Chang, The University of Chicago • Invited speaker: Rachel Mandelbaum, Carnegie Mellon University—“Galaxy Brain: AI Approaches to Large Sky Surveys” • Matiwos Mebratu, Stanford University—“Hybrid Prior Wavelet based Conditional Flow Matching Model (HyWave-CFM)” | Auditorium and Zoom |
| 5:15–5:30 p.m. | Day 2 wrap-up: Updates for the SkAI community Exploration of Emerging Research (SEER) program, Astro-AI glossary | 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.
