Project 9: Intelligent Scheduling for Astronomical Surveys

Lead PIs: Alex Drlica-Wagner (UC), Aravindan Vijayaraghavan (NU)
Collaborators: Emma Alexander (NU), Paul Chichura (UC), Ani Chiti (UC), Aleksandra Ćiprijanović (Fermilab), Alexander Ji (UC), Guilherme Limberg (UC), Adam Miller (NU), Gautham Narayan (UIUC), Brian Nord (Fermilab), Tanmay Sinha (NU)
Project Summary: This project has the following objectives: (1) develop reinforcement-learning (RL) algorithms for dynamic, real-time astronomical observation scheduling with deferred, multi-objective rewards; and (2) use active learning and weak-to-strong supervision to optimize target selection for population-level parameter inference. These objectives will be met by (1) leveraging state-of-the-art AI techniques, including RL, active learning, and conformal prediction; and (2) using ∼500k observations from the Dark Energy Camera (DECam) for model training and validation.

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.