University of Georgia

Graduate students named recipients of DOE fellowship

photo of Anna Doner
Anna Doner (Submitted photo)

Three Ph.D. students at UGA were named recipients of the 2020 Office of Science Graduate Student Research fellowship from the U.S. Department of Energy. Kenneth Allen, Anna Doner and Scott Oswald were recognized for outstanding accomplishments in academics and research that show the potential to make important contributions to the mission of the DOE Office of Science.

The SCGSR fellowship provides supplemental funds for recipients to conduct part of their thesis work at a host DOE laboratory in collaboration with a DOE scientist.

photo of Kenneth Allen
Kenneth Allen (Submitted photo)

Allen, a Ph.D. student in mathematics in the Franklin College of Arts and Sciences, researches data completion: When an array of data is incomplete, for example, what strategies can be used to complete the data as best as possible? His adviser is Ming-Jun Lai, UGA professor of mathematics, and he is completing a research assistantship with Lin Mu, assistant professor of mathematics. Allen will work with David Green at Oak Ridge National Laboratory in Oak Ridge, Tennessee.

“I am extremely excited and grateful to receive the SCGSR award. It will allow me to apply techniques developed in my research to large scale scientific data, as opposed to images or synthetic data,” Allen said. “Moreover, my research will potentially allow me to improve upon a computationally prohibitive step required for fusion simulation.

Doner, a Ph.D. student in chemistry in the Franklin College, is using automated software to discover new chemical reactions in combustion chemistry, which will improve modeling needed for engine design. Her adviser is Brandon Rotavera, assistant professor with appointments in the College of Engineering and the department of chemistry in the Franklin College. Doner will work with Judit Zádor at the Combustion Research Facility at Sandia National Laboratories in Livermore, California.

“I am excited to visit and work in a national laboratory, which has been a major goal of mine for a long time,” she said. “This fellowship will provide software training that is critical to both my dissertation work here at UGA and my future career.”

photo of Scott Oswald
Scott Oswald (Submitted photo)

Oswald, a Ph.D. student at the Warnell School of Forestry and Natural Resources, works with adviser Doug Aubrey, associate professor at Warnell and the Savannah River Ecology Lab. Oswald studies how sugar and starch concentrations change over the course of a year after a drought. Accumulation of sugar and starch appears to help plants survive stressful periods like drought as well as periods of low photosynthesis like winter. Describing how these processes are regulated might allow scientists to predict when plants are resilient to stressors.

Oswald will work at Oak Ridge National Laboratory, under the supervision of Dan Ricciuto and Jeff Warren, on a project with two related goals.

“The first is improve how large ecosystem models represent sugar and starch dynamics to better predict how plants respond to future climates. The second is to develop a framework for those dynamics using ecological and evolutionary theory,” he said. “This fellowship is a good opportunity to receive mentorship and guidance about developing the ability to make connections between my background in mathematical biology and experimental observations.”

Allen, Doner and Oswald are part of a cohort of 78 graduate students, representing 26 states, that were selected for the fellowship based on merit peer review by external scientific experts.

SCGSR awardees work on research projects of significant importance to the Office of Science mission and that address societal challenges at a national and international scale. Projects in this cohort cover topics including fundamental studies for energy sciences, earth systems modeling, environmental system science, advanced accelerator and detector research, nuclear physics, enabling R&D for fusion energy, microelectronics, machine learning, quantum information science and data science.