James E. Bevins

Lt Col James E. Bevins is an Adjunct Assistant Professor of Nuclear Engineering at the Air Force Institute of Technology (AFIT), where he has held the position since 2017. He is the recipient of the Air Force Technical Applications Endowed Term Chair for Nuclear Treaty Monitoring (2018) and has been actively involved in the National Science Foundation Graduate Fellowship (2014–2017). His academic affiliations include AFIT and the University of California, Berkeley, where he earned his Ph.D. in Nuclear Engineering in 2017. Prior to his doctoral studies, he received his B.S. (2009) and M.S. (2011) in Nuclear Engineering from the University of Tennessee and AFIT, respectively.

His research focuses on advanced radiation detection methods, neutron spectra modeling, nuclear forensics, and weapon effects analysis for national security applications. Specific projects include developing customizable neutron spectra for treaty monitoring, optimizing rotating scatter mask systems for directional radiation detection, and applying machine learning to signal analysis in nuclear environments. He has also investigated asteroid deflection strategies using neutron energy simulations.

Bevins has been recognized with numerous awards, including the 2020 Air Education and Training Command Educator of the Year, the 2019 Tau Beta Pi Outstanding Thesis Advisor Award, and multiple Air Force Meritorious Service Medals. His work spans collaborations with Sandia National Laboratories, the National Ignition Facility (NIF), and the 88-Inch Cyclotron at Berkeley, emphasizing applied nuclear science and defense-oriented research.

As an educator, he has advised 4 PhD students and 8 M.S. students, with ongoing collaborations. His grants and projects include 8 research grants from organizations like the Air Force Technical Applications Center and the NSF. Bevins has contributed to labs such as the GENESIS spectrometer and the ATHENA radiation environment platform, advancing neutron spectroscopy and detector technology. His current efforts include refining metaheuristic optimization algorithms (e.g., Gnowee) and exploring nuclear data covariance for radiation transport simulations.