Influence modeling: Mathematical programming representations of persuasion under either risk or uncertainty. - William N. Caballero; Brian J. Lunday (Eur. J. Oper. Res., 2019)

Robust influence modeling under structural and parametric uncertainty: An Afghan counternarcotics use case. - William N. Caballero; Brian J. Lunday (Decis. Support Syst., 2020)

Poisoning finite-horizon Markov decision processes at design time. - William N. Caballero; Phillip R. Jenkins; Andrew J. Keith (Comput. Oper. Res., 2021)

Identifying behaviorally robust strategies for normal form games under varying forms of uncertainty. - William N. Caballero; Brian J. Lunday; Richard P. Uber (Eur. J. Oper. Res., 2021)

Modeling Ethical and Operational Preferences in Automated Driving Systems. - William N. Caballero; Roi Naveiro; David Ríos Insua (Decis. Anal., 2022)

Transportation Labor Cost Reduction via Vehicle Platooning: Alternative Models and Solution Methods. - William N. Caballero; Florian Jaehn; Brian J. Lunday (Transp. Sci., 2022)

Managing Driving Modes in Automated Driving Systems. - David Ríos Insua; William N. Caballero; Roi Naveiro (Transp. Sci., 2022)

Multipolar Security Cooperation Planning: A Multiobjective, Adversarial-Risk-Analysis Approach. - William N. Caballero; Ethan Gharst; David Banks; Jeffery D. Weir (Decis. Anal., 2023)

Decision support issues in automated driving systems. - William N. Caballero; David Ríos Insua; David Banks (Int. Trans. Oper. Res., 2023)

Toward automated instructor pilots in legacy Air Force systems: Physiology-based flight difficulty classification via machine learning. - William N. Caballero; Nathan B. Gaw; Phillip R. Jenkins; Chancellor Johnstone (Expert Syst. Appl., 2023)

Adversarial Risk Analysis for Automated Lane-Changing in Heterogeneous Traffic. - Roi Naveiro; David Ríos Insua; William N. Caballero (ADT, 2024)

On Large Language Models in National Security Applications. - William N. Caballero; Phillip R. Jenkins (CoRR, 2024)

Indiscriminate Disruption of Conditional Inference on Multivariate Gaussians. - William N. Caballero; Matthew LaRosa; Alexander Fisher; Vahid Tarokh (CoRR, 2024)

Responsible machine learning for United States Air Force pilot candidate selection. - Devin Wasilefsky; William N. Caballero; Chancellor Johnstone; Nathan B. Gaw; Phillip R. Jenkins (Decis. Support Syst., 2024)

Regulating the rebound effect in the traveling purchaser problem. - William N. Caballero; Brian J. Lunday; Finn Meissner (Eur. J. Oper. Res., 2024)

Manipulating hidden-Markov-model inferences by corrupting batch data. - William N. Caballero; José Manuel Camacho; Tahir Ekin; Roi Naveiro (Comput. Oper. Res., 2024)

Poisoning Bayesian Inference via Data Deletion and Replication. - Matthieu Carreau; Roi Naveiro; William N. Caballero (AISTATS, 2025)

Bayesian Graph Traversal. - William N. Caballero; Phillip R. Jenkins; David Banks; Matthew J. Robbins (CoRR, 2025)