Project 3: A Universal Forecaster for Astronomical Light Curves, and Other Out-of-Domain Time-Series Data

Lead PIs: Han Liu (NU), Adam Miller (NU)
Collaborators: Hong-Yu Chen (NU), Weijian Li (NU), Qinjie Lin (NU), Nabeel Rehemtulla (NU), Ved Shah (NU), Padma Venkatraman (UIUC)
Project Summary: This project seeks to predict nonuniformly sampled time-series data using artificial intelligence with uncertainty quantification. The main goal is astronomical time-series data, mainly from stars within the Zwicky Transient Facility (ZTF) survey, but ultimately applicable to Rubin/Legacy Survey of Space and Time (LSST) and even other domains.

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.