Major Phillip R. Jenkins, Assistant Professor of Operations Research
Major Phillip R. Jenkins is an Assistant Professor of Operations Research in the Department of Operational Sciences, Air Force Institute of Technology (AFIT). He holds a bachelor’s degree in Mathematics from Ohio University as well as a master’s and a doctoral degree in Operations Research from AFIT. He commissioned through the Air Force Reserve Officer Training Corps in 2012 as an Operations Research Analyst. Prior to obtaining his graduate degrees from AFIT, Major Jenkins was assigned to Air Force Global Strike Command A9 where he served as a Long Range Systems Strike Analyst and as the Chief of Force Structure Assessments from January 2013 to July 2015.
Education
Doctor of Philosophy (Ph.D.), Operations Research, Air Force Institute of Technology, 2019
Master of Science (M.S.) Operations Research, Air Force Institute of Technology, 2017; Distinguised Graduate
Bachelor of Science (B.S.), Mathematics, Ohio University, 2012
Awards
2021 HOT Article Award (Analytical Methods)
2021 Innovations in Nuclear Technology Research and Development Award (Department of Energy)
2020 Outstanding Young Member OR/MS Award (INFORMS Cincinnati-Dayton Chapter)
2019 Distinguished Graduate, Squadron Officer School (Air University)
2019 General Omar N. Bradley Research Fellowship in Mathematics (United States Military Academy)
2018 Richard H. Barchi Prize (Military Operations Research Society)
2017 Distinguished Graduate, M.S. in Operations Research Program (AFIT)
2016 Indoctrinated into Omega Rho (Operations Research Honor Society)
2016 Indoctrinated into Tau Beta Pi (Engineering Honor Society)
Publications
Jenkins, P.R., Caballero, W.N., and Hill, R.R. (2021). Predicting Success in United States Air Force Pilot Training using Machine Learning Techniques. Socio-Economic Planning Sciences (forthcoming, accepted 6 July 2021). DOI: https://doi.org/10.1016/j.seps.2021.101121.
Rao*, A.P, Jenkins, P.R., Vu, D.M., Auxier II, J.D., and Shattan, M.B. (2021). Rapid quantitative analysis of trace elements in plutonium alloys using a handheld laser-induced breakdown spectroscopy (LIBS) device coupled with chemometrics and machine learning. Analytical Methods,13 (30), 3368-3378. (2021 HOT Article Award Winner) DOI: https://doi.org/10.1039/D1AY00826A.
Forrest*, N.C., Hill, R.R., and Jenkins, P.R. (2021). An Air Force Pilot Training Recommendation System using Advanced Analytical Methods. INFORMS Journal on Applied Analytics (forthcoming, accepted 29 June 2021).
Caballero, W.N., Jenkins, P.R., and Keith, A.J. (2021). Poisoning Finite-Horizon Markov Decision Processes at Design Time. Computers and Operations Research, 129 (May), 1-17. DOI: https://doi.org/10.1016/j.cor.2020.105185.
Rao*, A.P, Jenkins, P.R., Auxier II, J.D., and Shattan, M.B. (2021). Comparison of machine learning techniques to optimize the analysis of plutonium surrogate material via a portable LIBS device. Journal of Analytical Atomic Spectrometry, 36 (2), 399-406. (2021 Department of Energy Innovations in Nuclear Technology Research and Development Award Winner). DOI: https://doi.org/10.1039/D0JA00435A.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2021). Approximate Dynamic Programming for the Military Aeromedical Evacuation Dispatching, Preemption-Rerouting, and Redeployment Problem. European Journal of Operational Research, 290 (1), 132-143. DOI: https://doi.org/10.1016/j.ejor.2020.08.004.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2021). Approximate Dynamic Programming for Military Medical Evacuation Dispatching Policies. INFORMS Journal on Computing, 33 (1), 2-26. DOI: https://doi.org/10.1287/ijoc.2019.0930.
Jenkins, P.R., Lunday, B.J., and Robbins, M.J. (2020). Robust, Multi-Objective Optimization for the Military Medical Evacuation Location-Allocation Problem. Omega, 97 (December), 102088, 1-12. DOI: https://doi.org/10.1016/j.omega.2019.07.004.
Robbins, M.J., Jenkins, P.R., Bastian, N.D., and Lunday, B.J. (2020). Approximate Dynamic Programming for the Aeromedical Dispatching Problem: Value Function Approximation Utilizing Multiple Level Aggregation. Omega, 91 (March), 102020, 1-17. DOI: https://doi.org/10.1016/j.omega.2018.12.009.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2018). Examining Military Medical Evacuation Dispatching Policies Utilizing a Markov Decision Process Model of a Controlled Queueing System. Annals of Operations Research, 271 (2), 641-678. DOI: https://doi.org/10.1007/s10479-018-2760-z.
* denotes student author.