10:00 - 10:05 - Opening remarks - Josh Speagle/Gwen Eadie (Stats/Astro)
10:05 - 10:25 - Large Language Models in Astronomy - Yuan-Sen Ting (ANU/OSU, Dunlap Visitor)
10:25 - 10:45 - Self-Supervised Learning of Stars with Transformers - Henry Leung (Astro)
10:45 - 11:05 - Using Graph Neural Networks and Simulation-Based Inference to Probe Cold Dark Matter Sub-halo Perturbations in Stellar StreamsPeter Ma (Astro/Stats)
11:05 - 11:20 - Break
11:20 - 11:30 - AI in Scientific Workflows - Rohan Alexander (Stats)
11:30 - 11:40 - AI and Human-Computer Interactions - Fanny Chevalier (Stats)
11:40 - 11:50 - AI and Pedagogy - Nathalie Moon (Stats)
11:50 - 12:30 - Invited Panel DiscussionRohan Alexander (Stats), Fanny Chevalier (Stats), & Nathalie Moon (Stats)
12:30 - 12:45 - Group Photo
12:45 - 13:45 - Catered Lunch
13:35 - 13:55 - Scaling Laws for Galaxy Images - Michael Walmsley (Dunlap)
13:55 - 14:15 - Flexible Models for Noisy Observations: a Blessing and a Curse - Reed Essick (CITA)
14:15 - 14:35 - Trustworthy/Interpretable AI - Qiang Sun (Stats)
14:35 - 14:50 - Break
14:50 - 14:57 - Inferring reionization history with quasar proximity zone data using simulation-based inference - Hanquing Chen (CITA)
14:57 - 15:04 - Closing the stellar labels gap: fully data-driven modelling of stellar spectra - Alex Laroche (Astro)
15:04 - 15:11 - Progenitors of Milky Way mass galaxies with JWST resolved photometry - Vivian Tan (Astro @ York)
15:11 - 15:18 - Using Stellar Catalogues for 3D Radiative Mapping of our Galaxy -Ioana Zelko (CITA)
15:18 - 15:25 - Detecting stellar flares in photometric data using hidden Markov models - Arturo Esquivel (CITA)
15:25 - 15:32 - Astrophysical transient detection applied to calcium imaging of the brain- Bolin Fan (Astro)
15:32 - 15:39 - Exploring Change-point Models and Functional Data Analysis: A Bayesian Perspective - Ana Carolina da Cruz (Stats)
15:39 - 15:46 - Making Mock Maps for the Line Intensity Mapping Experiments - Doğa Tolgay (CITA)
15:46 - 16:00 Break
16:00 - 16:20 - Satellite data and machine learning to assess environmental exposures for health studies - Meredith Franklin (Stats)
16:20 - 16:40 - Calibrated predictive distributions for photometric redshiftse - Biprateep Dey (Astro @ Pitt → Stats @ UofT)
16:40 - 16:45 - Closing remarks - Antonio Herrera Martin/Kevin McKinnon(Stats/Astro)
16:45 - 17:00 - Break + Workshop Wrap-Up