David Shih

Shih’s research aims to develop state-of-the-art AI/ML methods and apply them to large datasets from high energy physics and astronomy, in order to answer the big open questions of fundamental physics, such as: What is the nature dark matter? What new particles and forces exist beyond the Standard Model? Shih’s recent work has used cutting-edge neural network and generative AI architectures to invent new methods for anomaly detection, fast simulation, feature selection, and interpretable AI at the Large Hadron Collider; new discoveries of stellar streams and a new measurement of the local dark matter density using data from the Gaia Space Observatory; new discoveries of ultra-faint dwarf galaxies using the Hubble Space Telescope; and the first-ever application of simulation-based inference to pulsar timing arrays.