Research:

Weijia (Emma) Liu uses advanced artificial intelligence (AI), machine learning (ML), and physics-based simulations to study how ice and glaciers behave. The way ice moves at the continental scale of entire ice sheets (hundreds of km) is dictated by physics at the mm scale of ice crystals. This link between small-scale ice behavior and large-scale glacier movement is governed by ice rheology. Bridging this gap is challenging, but essential for improving how we model glacier flow and predict future changes.

Liu’s research builds that bridge. By combining data from radar observations (km scale), ice core samples (mm to m scale), and glacier modeling, her work uses AI/ML to connect insights across scales. In doing so, she aims to improve glacier modeling and foster stronger collaboration among radar scientists, ice core experts, and modelers, which are the three communities that often work separately due to the vast differences in data scale and governing physics.

Bio:

Weijia (Emma) Liu is an Eric and Wendy Schmidt AI in Science Fellow in the Department of Geophysical Science at the University of Chicago. She works with Prof. Meghana Ranganathan at the intersection of AI/ML and glacier modeling. Prior to this, she obtained her Ph.D. in the Geophysics Department at Stanford University in 2025 under the supervision of Prof. Jenny Suckale, where she studied shear localizations in glaciers using high-performance computing and ML.