Major Phillip R. Jenkins, Adjunct Assistant Professor of Operations Research
Major Phillip R. Jenkins is an Adjunct Assistant Professor of Operations Research in the Department of Operational Sciences, Air Force Institute of Technology and a student at the School of Advanced Air and Space Studies at Maxwell AFB, Alabama.
Maj Jenkins received his commission in December 2012 after graduating from Ohio University with a Bachelor of Science in Mathematics. He began his Air Force career at Air Force Global Strike Command at Barksdale AFB, Louisiana, serving initially as a Long Range Systems Strike Analyst and later as the Chief of Force Structure Assessments. In August 2015, Maj Jenkins pursued further education at the Air Force Institute of Technology at Wright-Patterson AFB, Ohio, earning a Master of Science in Operations Research in March 2017 and a Doctor of Philosophy in Operations Research in June 2019. Following his doctoral studies, Maj Jenkins continued at the Air Force Institute of Technology as a faculty member, division chief, and deputy director until June 2023. Prior to his current position, Maj Jenkins was an Air Command and Staff College student at Maxwell AFB, Alabama.
Maj Jenkins deployed to the 609th Air Operations Center in 2022, serving as the Deputy Division Chief of the Operational Assessment Team in the Strategy Division.
(Current as of May 2024)
Education
2012 Bachelor of Science, Mathematics, Ohio University
2017 Distinguished Graduate, Master of Science, Operations Research, Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio
2019 Doctor of Philosophy, Operations Research, Air Force Institute of Technology, Wright-Patterson AFB, Ohio
2019 Distinguished Graduate, Squadron Officer School, Maxwell AFB, Ala.
2022 Air Command and Staff College, Maxwell AFB, Ala., by correspondence
2024 Top Graduate, Master of Military Operational Art and Science, Air Command and Staff College, Maxwell AFB, Ala.
Awards
2024 Top Graduate (#1/489), Air Command and Staff College (Air University)
2024 Distinguished Graduate (top 10%), Air Command and Staff College (Air University)
2024 Commandant’s Award for Excellence, Air Command and Staff College (Air University)
2024 Air Force Surgeon General Award (Department of the Air Force)
2023 Koopman Prize (INFORMS Military and Security Society)
2021 Field Grade Analyst of the Year (Department of the Air Force)
2021 Field Grade Officer of the Year (AFIT/EN)
2021 USAF-MIT AI Accelerator Datathon: Cognitive State Assessment in Pilots (Air Force Chief Data Office)
Overall Winner, Flight Scenario Difficulty Classification
Runner-up, Pilot Error Regression
Most Innovative Approach
Most Interpretable Model
Best Pitch
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)
2020 3x Company Grade Officer of the Quarter (AFIT/EN)
2019 Company Grade Officer of the Year (AFIT/EN)
2019 Company Grade Officer of the Quarter (AFIT/EN)
2019 Outstanding Performer (Pacific-Sentry 19-2)
2019 Distinguished Graduate (top 10%), Squadron Officer School (Air University)
2019 General Omar N. Bradley Research Fellowship in Mathematics (United States Military Academy)
2018 PhD Student Company Grade Officer of the Year (AFIT/EN)
2018 Seth Bonder Scholarship for Applied Operations Research in Military (INFORMS)
2018 Richard H. Barchi Prize (Military Operations Research Society)
2018 General Omar N. Bradley Research Fellowship in Mathematics (United States Military Academy
2017 Distinguished Graduate (top 10%), AFIT M.S. in Operations Research Program (Air University)
2016 Indoctrinated into Omega Rho (Operations Research Honor Society)
2016 Indoctrinated into Tau Beta Pi (Engineering Honor Society)
2015 Nuclear Deterrence Operations Team of the Year (Department of the Air Force)
2015 General Benjamin Oliver Davis Jr. Management Engineering Team Award (Department of the Air Force)
2015 Company Grade Officer of the Quarter (AFGSC A5/8/9)
2014 Company Grade Analyst of the Year (Air Force Global Strike Command)
2014 Company Grade Officer of the Year (Air Force Global Strike Command A5/8/9)
2014 Lance P. Sijan Award (Air Force Global Strike Command A5/8/9)
2014 Company Grade Officer of the Quarter (Air Force Global Strike Command A5/8/9)
Publications
PEER-REVIEWED JOURNAL ARTICLES (23)
Long*, C.G., Lunday, B.J., and Jenkins, P.R. (2024). Spatiotemporal Network Vulnerability Identification for the Material Routing Problem: a Bilevel Programming Approach. Military Operations Research Journal (forthcoming).
Caballero, W.N., Cooley*, J.P., Banks, D.L., and Jenkins, P.R. (2024). A Behavioral Approach to Stochastic Bayesian Security Games. Annals of Applied Statistics, 18 (1), 199-223. DOI: https://doi.org/10.1214/23-AOAS1786.
Gelbard*, A.G., Jenkins, P.R., and Robbins, M.J. (2024). Enhancing Military Medical Evacuation Dispatching with Armed Escort Management: Comparing Model-Based Reinforcement Learning Approaches. Journal of Defense Modeling and Simulation (forthcoming). DOI: https://doi.org/10.1177/154851292412297.
Wasilefsky*, D.C., Caballero, W.N., Johnstone, C.A., Jenkins, P.R., Gaw, N.B. (2024). Responsible Machine Learning for United States Air Force Pilot Candidate Selection. Decision Support Systems, 180 (May), 114198. DOI: https://doi.org/10.1016/j.dss.2024.114198.
Frial*, V.B., Jenkins, P.R., Robbins, M.J. (2024). Characterizing military medical evacuation dispatching and delivery policies via a self-exciting spatio-temporal Hawkes process model. Journal of the Operational Research Society, 75 (7), 1239-1260. DOI: https://doi.org/10.1080/01605682.2023.2239884.
Caballero, W.N., Gaw, N.B., Jenkins, P.R., Johnstone, C.A. (2023). Toward Automated Instructor Pilots in Legacy Air Force Systems: Physiology-based Flight Difficulty Classification via Machine Learning. Expert Systems with Applications, 231 (November), 120711. DOI: https://doi.org/10.1016/j.eswa.2023.120711.
Rodriguez*, C.A., Jenkins, P.R., Robbins, M.J. (2023). Solving the Joint Military Medical Evacuation Problem via a Random Forest Approximate Dynamic Programming Approach. Expert Systems with Applications, 221 (July), 119751. DOI: https://doi.org/10.1016/j.eswa.2023.119751.
Rao*, A.P., Jenkins, P.R., Pinson*, R.E., Auxier II, J.D., Shattan, M.B., and Patnaik, A.K. (2023). Machine Learning in Analytical Spectroscopy for Nuclear Diagnostics. Applied Optics, 62 (6), A83-A109. DOI: https://doi.org/10.1364/AO.482533.
Pinson*, R.E., Giminaro, A.V., Dugan, C.L., Jenkins, P.R., and Patnaik, A.K. (2023). LIBS and Raman Spectroscopy in Tandem with Machine Learning for Interrogating Weatherization of Lithium Hydride. Applied Optics, 62 (6), 1528-1536. DOI: https://doi.org/10.1364/AO.482304.
Rao*, A.P, Jenkins, P.R., Auxier II, J.D., Shattan, M.B., and Patnaik, A.K. (2022). Enabling orders of magnitude sensitivity improvement for quantification of Ga in a Ce matrix with a compact Echelle spectrometer. Journal of Analytical Atomic Spectrometry, 37 (10), 1975-1980. DOI: https://doi.or/10.1039/D2JA00179A.
Crumpacker*, J.B, Robbins, M.J., Jenkins, P.R. (2022). An Approximate Dynamic Programming Approach for Solving an Air Combat Maneuvering Problem. Expert Systems with Applications, 203 (October), 117448. DOI: https://doi.org/10.1016/j.eswa.2022.117448.
Rao*, A.P, Jenkins, P.R., Auxier II, J.D., Shattan, M.B., and Patnaik, A.K. (2022). Analytical comparisons of handheld LIBS and XRF devices for rapid quantification of gallium in plutonium surrogate matrix. Journal of Analytical Atomic Spectrometry, 37 (5), 1090-1098. DOI: https://doi.org/10.1039/D1JA00404B.
Rao*, A.P, Jenkins, P.R., Auxier II, J.D., Shattan, M.B., and Patnaik, A.K. (2022). Development of advanced machine learning models for analysis of plutonium surrogate optical emission spectra. Applied Optics, 61 (7), D30-D38. DOI: https://doi.org/10.1364/AO.444093.
Jenkins, P.R., Caballero, W.N., and Hill, R.R. (2022). Predicting Success in United States Air Force Pilot Training using Machine Learning Techniques. Socio-Economic Planning, 79 (February), 101121, 1-14. 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. (2022). An Air Force Pilot Training Recommendation System using Advanced Analytical Methods. INFORMS Journal on Applied Analytics, 52 (2), 198-209. (2023 INFORMS Military and Security Society Koopman Prize Winner). DOI: https://doi.org/10.1287/inte.2021.1099.
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. (2018 MORS Richard H. Barchi Prize Winner). 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.
REFEREED CONFERENCE PROCEEDINGS (2)
Rao*, A.P, Jenkins, P.R., Patnaik, A.K. (2022). Enabling High-Fidelity Spectroscopic Analysis of Plutonium with Machine Learning. In Proceedings Optical Sensors and Sensing Congress 2022 (AIS, LACSEA, Sensors, ES).
Graves*, E.S., Jenkins, P.R., and Robbins, M.J. (2021). Analyzing the Impact of Triage Classification Errors on Military Medical Evacuation Dispatching Policies. In Proceedings of the 2021 Winter Simulation Conference.
* denotes student author.
REFEREED BOOK CHAPTERS (1)
Jenkins, P.R., Robbins, M.J. (2023). Military and Security Applications: Medical Evacuation. The Encyclopedia of Optimization. DOI: https://doi.org/10.1007/978-3-030-54621-2_760-1.
MONOGRAPHS (2)
Jenkins, P.R. (2019). Strategic Location and Dispatch Management of Assets in a Military Medical Evacuation Enterprise. Ph.D. dissertation, Air Force Institute of Technology.
Jenkins, P.R. (2017). Using Markov Decision Processes with Heterogeneous Queueing Systems to Examine Military MEDEVAC Dispatching Policies. Master’s thesis, Air Force Institute of Technology.
OTHER PUBLICATIONS (5)
Jenkins, P.R., and Weir, J.D. (2023). Enhancing Military Operations through the Integration of Operations Analysis Officers into Air Operations Center Divisions and Air Force Wings. Phalanx, 56 (3), 14-17.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2023). Tutorial -- Transforming a Continuous-Time Markov Decision Process to an Equivalent Discrete-Time Markov Decision Process via Uniformization, with Application to Military Medical Evacuation. Medium, 2023.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2021). Optimising Aerial Military Medical Evacuation Dispatching Decisions via Operations Research Techniques. BMJ Military Health, 169 (e1), e90-e92. DOI: http://dx.doi.org/10.1136/bmjmilitary-2020-001631.
Jenkins, P.R., Lunday, B.J., and Robbins, M.J. (2020). Artificial Intelligence for Medical Evacuation in Great-Power Conflict. War on the Rocks, 2020.
Jenkins, P.R., Lunday, B.J., and Robbins, M.J. (2020). Aerial MEDEVAC Operations Decision-making under Uncertainty to Save Lives. Phalanx, 53 (1), 63-66.