Dr. William N. Caballero, Assistant Professor of Data Science

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Dr. William N. Caballero is an Assistant Professor of Data Science with the Department of Operational Sciences, Air Force Institute of Technology (AFIT).

His research focuses on providing decision support in uncertain, multi-agent environments through the development of statistical and mathematical models, as well as the design of accompanying optimization routines. This broad focus necessitates an eclectic methodological perspective, ranging from deterministic and stochastic optimization to Bayesian analysis and interpretable machine learning, thereby positioning his work at the intersection of statistics and operations research. His recent work leverages Bayesian decision analysis for myriad security problems and applies modern data science methods to defense-related problems. 

Education

Doctor of Philosophy, Operations Research, Air Force Institute of Technology, 2019

Master of Science, Operations Research, Air Force Institute of Technology, 2017

Bachelor of Science, Industrial Engineering, University of Houston, 2011

Awards

• Seiler Award (USAFA/DFMS), Research Excellence in Mathematical Sciences; 2023
• Clemen–Kleinmuntz Decision Analysis Best Paper Award, Finalist; 2022
• USAF-MIT AI Accelerator Datathon: Cognitive State Assessment in Pilots; 2021
  • Overall Winner, Flight Scenario Difficulty Classification
  • Runner-up, Pilot Error Regression
  • Most Innovative Approach
  • Most Interpretable Model
  • Best Pitch
• United States Air Force Academy, Field Grade Officer of the Quarter; 2021
• Basic Sciences Division, USAFA, Field Grade Officer of the Quarter; 2021 
• Department of Mathematical Sciences, USAFA, Field Grade Officer of the Quarter (x2); 2021 and 2024
• 612th Air Operations Center (Strategy Division), Company Grade Officer of the Quarter; 2020
• Air Combat Command, Company Grade Analyst of the Year; 2019
• Distinguished Graduate; Air Force Squadron Officer School; 2019
• General Omar Nelson Bradley Fellow; 2018
• Inductee, Omega Rho, Operations Research Honor Society; 2016 Inductee
• Tau Beta Pi, Operations Research Honor Society; 2016
• Distinguished Graduate; Air Force Institute of Technology; 2015
• Air Force Institute of Technology, Company Grade Officer of the Quarter (x4) 2015-2019
• AF/A9 Lance P. Sijan Award; 2014
• AF/A9 Mission Support Professional of the Year; 2014
• Headquarter Air Force A9, Company Grade Officer of the Quarter (x2); 2013 and 2015
• Distinguished Graduate; Air Force Officer Training School; 2012

Publications

Journal Articles

1. Caballero, W.N., Jenkins, P.R. (2025), On Large Language Models in National Security Applications, Stat, 14: e70057, Available at: https://doi.org/10.1002/sta4.70057
2. Wasilefsky, D., Caballero, W.N., Johnstone, C., Gaw, N., Jenkins, P.R. (2024), Responsible Machine Learning for United States Air Force Pilot Candidate Selection. Decision Support Systems, 180. Available at: https://doi.org/10.1016/j.dss.2024.114198
3. Caballero, W.N., Cooley, J., Banks, D. and Jenkins, P.R. (2024), A Behavioral Approach to Repeated Bayesian Security Games. Annals of Applied Statistics, 18 (1), Available at: https://doi.org/10.1214/23-AOAS1786
4. Caballero, W.N., Camacho, J.M., Ekin, T., Naviero, R. (2023), Manipulating Hidden-Markov-Model Inferences by Poisoning Batch Data. Computers & Operations Research. 162, Available at: https://doi.org/10.1016/j.cor.2023.106478
5. Caballero, W.N., Gaw, N., Jenkins, P.R., Johnstone, C. (2023), Toward Automated Instructor Pilots in Legacy Air Force Systems: Physiology-based Flight Difficulty Classification via Machine Learning. Expert Systems with Applications, 231, Available online at: https://doi.org/10.1016/j.eswa.2023.120711
6. Caballero, W.N., Rios-Insua, D., Naviero, R. (2023) Some Statistical Challenges in Automated Driving Systems. Applied Stochastic Models in Business and Industry. 39 (5), 629-652. Available online at: https://doi.org/10.1002/asmb.2765
7. Caballero, W.N., Gharst, E., Banks, D., Weir, J.D. (2022) Multipolar Security Cooperation Planning: A Multi-objective Adversarial Risk Analysis Approach. Decision Analysis, 20 (1), 16-39. Available at: https://doi.org/10.1287/deca.2022.0458
8. Caballero, W. N., Meissner, F., Lunday, B.J. (2022), Regulating the Rebound Effect in the Traveling Purchaser Problem. European Journal of Operational Research. Available online at: https://doi.org/10.1016/j.ejor.2022.06.045
9. Caballero, W.N., Banks, D.L., Wu, K. (2022) Defense and Security Planning under Resource Uncertainty and Multi-period Commitments. Naval Research Logistics. 69 (7), 1009-1026. Available online at: https://doi.org/10.1002/nav.22071
10. Caballero, W. N., Jaehn, F., Lunday, B.J. (2022), Transportation Labor Cost Reduction via Vehicle Platooning: Alternative Models and Solution Methods. Transportation Science. Available online at: https://doi.org/10.1287/trsc.2021.1110
11. Rios-Insua, D., Caballero, W.N., Naviero, R. (2021) Managing Driving Modes in Level-3 and -4 Automated Driving Systems, Transportation Science, 56 (5), 1259-1278. Available online at: https://doi.org/10.1287/trsc.2021.1110.
12. Caballero, W.N., Naviero, R., Rios-Insua, D. (2021) Modeling Ethical and Operational Preferences in Automated Driving Systems. Decision Analysis, 19(1), 21-43. Available online at: https://doi.org/10.1287/deca.2021.0441.
13. Jenkins, P.R., Caballero, W.N., Hill, R.R. (2021) Predicting Success in United States Air Force Pilot Training using Machine Learning. Socio-Economic Planning Sciences, 79, Available online at: https://doi.org/10.1016/j.seps.2021.101121.
14. Caballero, W.N., Rios Insua, D., Banks, D.L. (2021) Decision Support Issues in Automated Driving Systems. International Transactions in Operational Research, 30 (3), 1216-1244. Available online at: https://doi.org/10.1111/itor.12936.
15. Caballero, W. N., Jenkins, P. R., & Keith, A.J. (2021) Poisoning Finite-Horizon Markov Processes at Design Time. Computers & Operations Research, 129, Available online at: https://doi.org/10.1016/j.cor.2020.105185.
16. Caballero, W. N., Lunday, B. J., & Uber, R. P. (2021) Identifying Behaviorally Robust Strategies for Normal Form Games under Varying Forms of Uncertainty. European Journal of Operational Research, 288 (3), 971-982. Available online at: https://doi.org/10.1016/j.ejor.2020.06.022.
17. Caballero, W. N., Lunday, B. J., & Ahner, D. K. (2020) Incentive Compatible Cost Sharing of a Public Good with Probabilistic Inspection and Penalties for Misrepresentation. Group Decision and Negotiation, 288, 1021-1055. Available online at: https:// 10.1007/s10726-020-09693-z.
18. Caballero, W. N., Lunday, B. J., & Deckro, R. F. (2020) Leveraging Behavioral Game Theory to Inform Military Operations Planning. Military Operations Research, 25 (1) 5-22.
19. Caballero, W. N., & Lunday, B. J. (2020) Robust Influence Modeling under Structural and Parametric Uncertainty: An Afghan Counternarcotics Use Case. Decision Support Systems, 128, 1- 11. Available online at: https://doi.org/10.1016/j.dss.2019.113161.
20. Caballero, W. N., Lunday, B. J., Deckro, R. F., & Pachter, M. (2020) Informing National Security Policy by Modeling Adversarial Inducement and its Governance. Socio-Economic Planning Sciences, 69, 1-15. Available online at: https://doi.org/10.1016/j.seps.2019.04.006.
21. Caballero, W. N. & Lunday, B. J. (2019) Influence Modeling: Mathematical Programming Representations of Persuasion under Either Risk or Uncertainty. European Journal of Operational Research, 278 (1), 266-282. Available online at: https://doi.org/10.1016/j.ejor.2019.04.006.

Machine Learning & Artificial Intelligence Conference Proceedings 

22. Carreau, M., Naviero, R., Caballero, W.N. (2025), Poisoning Bayesian Inference via Data Deletion and Replication. AISTATS 2025, Mai Khao, Thailand.

Engineering Conference Proceedings 

23. Caballero, W.N., Friend, M., Blasch, E. (2021) Adversarial Machine Learning and Adversarial Risk Analysis in Multi-Source Command and Control. SPIE Conference on Signal Processing, Sensor/Information Fusion, and Target Recognition, April 12-16, 2021, Digital Symposium.
24. Caballero, W. N., Kline, A. G., & Lunday, B. J. (2018) Challenges and Solutions with Exponentiation Constraints using Decision Variables via the BARON Commercial Solver. In Proceedings of the 2018 Industrial and Systems Engineering Annual Conference (IISE), May 19-22, 2018, Orlando, FL. Available online at https://www.xcdsystem.com/iise/2018_proceedings/papers/SubmitFinalPaper_1334_0302010321.pdf
25. Kline, A. G., Caballero, W. N., & Ahner, D. A. (2018) False Optimality of Integer Programs with Exponential Decision Variables. In Proceedings of the 2018 Industrial and Systems Engineering Annual Conference (IISE), May 19-22, 2018, Orlando, FL. Available online at https://www.xcdsystem.com/iise/2018_proceedings/papers/SubmitFinalPaper_1341_0302112728.pdf  

Economics and Management Science Conference Proceedings

26. Naviero, R., Rios-Insua, D., Caballero, W.N. (2024) Adversarial Risk Analysis for Automated Lanechanging in Heterogeneous Traffic. 8 th International Conference on Algorithmic Decision Theory. Rutgers University, October 14-16, 2024, Piscataway, NJ.
27. Donnel, S., Caballero, W.N., Lunday, B.J. (2024) The Effects Of Information Presentation and Situational Complexity On Effective Decisionmaking. 2024 Western Decision Science Institute (WDSI) Annual Conference. April 2-5, 2024. Santa Rosa, CA.