Fruit flies, algorithms and light offer lessons in how complex organisms learn.
Knowing the unknowns
A Georgia Tech fellow models renewable energy and other problems with ever-changing unknowns.
Unpacking snow
A UC Berkeley fellow applies machine learning to snowpack monitoring and more.
Sculpting nature
A Harvard University fellowship recipient works to create quantum phases of matter.
Categorical imperative
A Montana State fellow charts a path from physics and modeling to a form of pure math called category theory.
Predicting chaos
A Caltech fellowship recipient works on the physics underlying turbulence, or the chaotic gain of energy when fluids move in unpredictable ways.
Scale-tamer
A recent program alum interweaves large and small scales in wind-energy and ocean models.
Exploring electrons
At UC Berkeley, a fellow applies machine learning to sharpen microscopy.
Subduing software surprises
A Cornell University fellowship recipient works on methods for ensuring software functions as expected.
‘Crazy ideas’
A UCSD engineering professor and former DOE CSGF recipient combines curiosity and diverse research experiences to tackle nanoscale questions and energy applications.
Star treatment
A UT Austin-based fellow blends physics and advanced computing to reveal cosmic rays’ role in stellar events.
New home for science and tech talk
With the fifth season’s first episode, a DOE CSGF-sponsored podcast launches a website.
Bolt basics
A Rice University fellow simulates the ins and outs of the familiar fasteners in pursuit of lean machines.
‘Putting it all together’
A Vanderbilt University fellowship recipient applies math, physics and computation to sort out semiconductor defects.
Genomic field work
A UC Davis fellow combines computing, the corn genome and growing data to help farmers forecast biofortified crop production.
Tracking space debris
A Computational Science Graduate Fellowship recipient monitors threats to satellites in Earth’s ionosphere by modeling plasma waves.
Decisive achievement
A computational sciences fellow models COVID-19 virus variants and examines how people weigh complex decisions.
Learning climate
A Colorado State fellow employs machine learning for climate modeling, putting provenance behind predictions.
Statistically significant
A LANL statistician helps cosmologists and epidemiologists grasp their data and answer vital questions.
Planet-friendly plastics
A Los Alamos team applies machine learning to find environmentally benign plastics.
A split nanosecond
Sandia supercomputer simulations of atomic behavior under extreme conditions advances materials modeling.
A colorful career
Argonne’s Joe Insley combines art and computer science to build intricate images and animations from supercomputer simulations.
