Fellows’ Research

A Cornell University fellow develops strategies to extract more than correlations from algorithms’ predictions.

A University of Alabama fellow shows that AI models learn to simulate atomic interactions.

A University of Washington fellow learns about oceans, combining observation with large-scale simulations.

A UCSD fellow’s geodynamic model offers answers to stubborn questions about Venus’ surface.

A University of Maryland fellow models how infectious disease moves through populations.

Notable program alum Amanda Randles models blood circulation — and is a role model for beginning scientists.

Fruit flies, algorithms and light offer lessons in how complex organisms learn.

An NYU fellow accelerates algorithms that run vital processes backward.

Models of semiconductor defects point to improved qubit reliability.

A Georgia Tech fellow models renewable energy and other problems with ever-changing unknowns.

A UC Berkeley fellow applies machine learning to snowpack monitoring and more.

A Harvard University fellowship recipient works to create quantum phases of matter.

A recent program alum interweaves large and small scales in wind-energy and ocean models.

At UC Berkeley, a fellow applies machine learning to sharpen microscopy.

A UC Davis fellow combines computing, the corn genome and growing data to help farmers forecast biofortified crop production.