Three students from the University of Tennessee–Oak Ridge Innovation Institute’s Bredesen Center have been selected for the 2026 National Science Foundation Graduate Research Fellowship Program, one of the nation’s most prestigious awards supporting graduate research in science, technology, engineering and mathematics.
The NSF Graduate Research Fellowship Program recognizes and supports outstanding graduate students with the potential to make significant contributions to the nation’s scientific and engineering workforce.
The Bredesen Center’s 2026 recipients are:
- Daniel Perkins, Data Science and Engineering
- Ella Williams, Energy Science and Engineering
- David Levy, Energy Science and Engineering
“These fellowships speak to the caliber of students in the Bredesen Center and the strength of the UT–ORNL partnership,” said Brynn Voy, UT-ORII interim executive director and Bredesen Center director. “We’re proud to see Ella, David and Daniel earn this national recognition and look forward to the contributions they will make in the years ahead.”
Williams’ research focuses on all-solid-state batteries, advancing next-generation energy storage technologies that are safer and more efficient.
“I am honored to receive this fellowship supporting my research on energy-dense solid-state batteries through the advancement of lithium metal anodes,” Williams said. “This fellowship will support standardization and optimization of these critical materials through collaboration with leading researchers and world-class facilities, under the guidance of Dr. Guang Yang in the Energy Storage and Conversion Group at ORNL.”
Williams has been involved with research at ORNL for the past three years, beginning with summer internships under Yang, who is now her adviser.
Levy’s research focuses on the characterization of color center defects in diamond under various environmental conditions to engineer better sensors. His advisor is Benjamin Lawrie, an ORNL senior research scientist and director for the Heterogeneous Quantum Systems Initiative.
Levy said he hopes to develop these systems further for integration into the quantum networks at ORNL.
Perkins is developing advanced artificial intelligence frameworks using graph neural networks and multi-agent deep reinforcement learning to improve real-time emergency response—helping guide individuals to safety during active threat scenarios. His work reflects the growing role of data science and AI in addressing critical national challenges. Perkins’ advisor is Subhadeep Chakraborty, an associate professor in UT’s Mechanical, Aerospace and Biomedical Engineering Dept.
“For my research, I am developing an AI-powered evacuation system for active shooter scenarios,” Perkins said. “The system combines computer vision, graph neural networks, and deep reinforcement learning to track threats in real time and guide evacuees along the safest and fastest routes.”
“The NSF funding will allow me to dedicate my full attention to this project, giving me freedom to pursue innovative and unexplored research directions,” he said.
