The U.S. Department of Energy’s Computational Science Graduate Fellowship (CSGF), jointly funded by the DOE Office of Science and NNSA, will receive a record number of new graduate students for 2022-23. The 33 new fellows represent 19 universities across the country and will learn to apply high-performance computing (HPC) to research across a range of fields, including atmospheric science, condensed matter physics, quantum information, and computational neuroscience.
“Office of Science is proud to support the training of a diverse and accomplished group of students to become leaders among the next generation of computational scientists,” said Barbara Helland, DOE Associate Director of Science for Advanced Scientific Computing Research. “As evidenced by the success of the current CSGF alumni, the new fellows’ research will advance efforts in a wide range of science and engineering topics that benefit Administration priorities and the American people.”
“This investment in the training of the people who will lead the application of high-performance computing to solve problems that will expand our understanding of key scientific issues in research areas fundamental to support the future nuclear deterrent, ensures a pipeline of highly-trained scientists and technicians,” said Dr. Mark Anderson, Assistant Deputy Administrator for Research, Development, Test, and Evaluation in NNSA’s Office of Defense Programs.
The DOE CSGF is one of six academic programs under DOE/NNSA; the other five being the Minority Serving Institution Partnership Program, the Tribal Education Partnership Program, the Joint Program in High Energy Density Laboratory Plasmas, the Stewardship Science Academic Alliances and the Predictive Science Academic Alliance Program.
The DOE CSGF includes a track for those pursuing an advanced degree in applied mathematics, statistics or computer science – in one of those departments or their academic equivalent − with research interests that help scientists use emerging high-performance systems more effectively. Students can also focus on issues in HPC as a broad enabling technology, rather than a particular science or engineering application.
As part of the program, fellows receive exceptional benefits, including a yearly stipend; full payment of university tuition and required fees; and an annual academic allowance. Renewable for up to four years, the fellowship is guided by a comprehensive program of study that requires focused coursework in the areas of science and engineering, computer science, applied mathematics, and HPC. It also includes a three-month practicum at one of 21 DOE laboratories or sites across the country.
Established in 1991, the CSGF has trained the top leaders in computational science, and with the addition of the 2022-23 class, nearly 600 students will have entered the fellowship. More than 450 now work in fields that support computing's capacity to address problems important to the nation’s future. For 2022-23, nearly half of the fellows self-identify as women and a similar proportion self-identify as a member of an underrepresented group.
Here are the newest fellows, their institutions, and their subject areas:
- Daniel Abdulah − Massachusetts Institute of Technology (Planetary Science)
- Caleb Adams − University of Texas at Austin (Ecohydrology)
- Christopher Anderson − University of Washington (Ecology)
- Elizabeth Bennewitz − University of Maryland College Park (Physics)
- Lucy Brown − Stanford University (Fluid Mechanics)
- Jackson Burns − Massachusetts Institute of Technology (Computational Science and Engineering)
- Nina Cao − Massachusetts Institute of Technology (Mechanical Engineering)
- Ashlynn Crisp − Portland State University (Mathematical Sciences)
- Grady Daniels − Massachusetts Institute of Technology (Statistics)
- Zachary Espinosa − University of Washington (Polar Climates and Sea Ice)
- Otto Fajen − Stanford University (Computational Chemistry)
- Joshua Fernandes − University of California, Berkeley (Chemical Engineering)
- Nina Filippova − University of Texas at Austin (Computational Astrophysics)
- Thomas Gade Jr. − University of Minnesota (Plasma Physics)
- Mary Gerhardinger − University of Pennsylvania (Natural Science)
- Gil Goldshlager − University of California, Berkeley (Applied Mathematics)
- McKenzie Hagen − University of Washington (Psychology)
- Michael Ito − University of Michigan (Computer Science)
- Alexander Johnson − Harvard University (Gravitational Physics)
- Katherine Keegan − Emory University (Computational Mathematics)
- McKenzie Larson − University of Colorado Boulder (Synoptic Meteorology)
- Jerry Liu − Stanford University (Computer Science)
- Kerri Lu − Massachusetts Institute of Technology (Computer Science)
- Storm Mata − Massachusetts Institute of Technology (Wind Energy and Atmospheric Boundary Layer Physics)
- Tristan Maxson − University of Alabama (Computational Chemistry/Catalysis)
- Franz O'Meally − California Institute of Technology (Engineering)
- Antonia Oprescu − Cornell University (Computer Science)
- Mansi Sakarvadia − University of Chicago (Computer Science)
- Carlyn Schmidgall − University of Washington (Physical Oceanography)
- Michael Tynes − University of Chicago (Computer Science)
- Grace Wei − University of California, Berkeley (Computational Materials Science)
- Emily Williams − Massachusetts Institute of Technology (Aeronautics and Astronautics)
- Joel Ye − Carnegie Mellon University (Computational Neuroscience)