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William N. Caballero Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
faculty
9 h-index
34 pubs
183 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
William N. Caballero's research focuses on the application of machine learning and artificial intelligence in complex operational and decision-making environments. His work has explored the development of automated systems for pilot training and selection within the United States Air Force, investigating physiology-based flight difficulty classification and responsible machine learning practices for candidate evaluation. Caballero has also investigated decision support issues and driving mode management in automated driving systems, as well as modeling ethical and operational preferences in these systems.
His research extends to national security applications of large language models. Caballero holds a h-index of 9 with 180 citations across 34 publications. His recent work includes publications in 2021, 2022, 2023, and a forthcoming publication in 2025, indicating continued activity in his research areas.
Metrics
- h-index: 9
- Publications: 34
- Citations: 183
Selected Publications
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Poisoning Bayesian Inference via Data Deletion and Replication (2025)
Collaboration Network
Top Collaborators
Roi Naveiro
CUNEF Universidad
9 shared publications
- Modeling Ethical and Operational Preferences in Automated Driving Systems
- Managing Driving Modes in Automated Driving Systems
- Manipulating hidden-Markov-model inferences by corrupting batch data
- Some statistical challenges in automated driving systems
- Adversarial Risk Analysis for Heterogeneous Traffic Management
Showing 5 of 9 shared publications
David Rı́os Insua
Institute of Mathematical Sciences (ES)
8 shared publications
- Decision support issues in automated driving systems
- Modeling Ethical and Operational Preferences in Automated Driving Systems
- Managing Driving Modes in Automated Driving Systems
- Some statistical challenges in automated driving systems
- Adversarial Risk Analysis for Heterogeneous Traffic Management
Showing 5 of 8 shared publications
Phillip R. Jenkins
Wright-Patterson Air Force Base (US)
8 shared publications
- Predicting success in United States Air Force pilot training using machine learning techniques
- Toward automated instructor pilots in legacy Air Force systems: Physiology-based flight difficulty classification via machine learning
- Responsible machine learning for United States Air Force pilot candidate selection
- On Large Language Models in National Security Applications
- Toward Automated Instructor Pilots in Legacy Air Force Systems: Physiology-Based Flight Difficulty Classification Via Machine Learning
Showing 5 of 8 shared publications
David Banks
Statistical and Applied Mathematical Sciences Institute (US)
4 shared publications
- Decision support issues in automated driving systems
- Defense and security planning under resource uncertainty and multi‐period commitments
- Multipolar Security Cooperation Planning: A Multiobjective, Adversarial-Risk-Analysis Approach
- Bayesian Graph Traversal
Brian J. Lunday
4 shared publications
- Regulating the rebound effect in the traveling purchaser problem
- Transportation Labor Cost Reduction via Vehicle Platooning: Alternative Models and Solution Methods
- Military and Security Applications: Behavioral Modeling
- Posterior Attraction with Exponential-Family Likelihoods and Their Conjugate Priors
Chancellor Johnstone
Wright-Patterson Air Force Base (US)
4 shared publications
- Toward automated instructor pilots in legacy Air Force systems: Physiology-based flight difficulty classification via machine learning
- Responsible machine learning for United States Air Force pilot candidate selection
- Toward Automated Instructor Pilots in Legacy Air Force Systems: Physiology-Based Flight Difficulty Classification Via Machine Learning
- Student-Pilot Error Prediction via Multimodal Physiological Signals and Tree-Based Models
Nathan Gaw
Wright-Patterson Air Force Base (US)
3 shared publications
- Toward automated instructor pilots in legacy Air Force systems: Physiology-based flight difficulty classification via machine learning
- Toward Automated Instructor Pilots in Legacy Air Force Systems: Physiology-Based Flight Difficulty Classification Via Machine Learning
- Student-Pilot Error Prediction via Multimodal Physiological Signals and Tree-Based Models
Matthew LaRosa
Duke University (US)
2 shared publications
- Indiscriminate disruption of conditional inference on multivariate Gaussians
- Indiscriminate Disruption of Conditional Inference on Multivariate Gaussians
Alexander A. Fisher
Statistical and Applied Mathematical Sciences Institute (US)
2 shared publications
- Indiscriminate disruption of conditional inference on multivariate Gaussians
- Indiscriminate Disruption of Conditional Inference on Multivariate Gaussians
Vahid Tarokh
Duke University (US)
2 shared publications
- Indiscriminate disruption of conditional inference on multivariate Gaussians
- Indiscriminate Disruption of Conditional Inference on Multivariate Gaussians
Raymond R. Hill
1 shared publication
- Predicting success in United States Air Force pilot training using machine learning techniques
Finn Meissner
1 shared publication
- Regulating the rebound effect in the traveling purchaser problem
Florian Jaehn
Helmut Schmidt University (DE)
1 shared publication
- Transportation Labor Cost Reduction via Vehicle Platooning: Alternative Models and Solution Methods
Keru Wu
Statistical and Applied Mathematical Sciences Institute (US)
1 shared publication
- Defense and security planning under resource uncertainty and multi‐period commitments
Ethan Gharst
United States Air Force Academy (US)
1 shared publication
- Multipolar Security Cooperation Planning: A Multiobjective, Adversarial-Risk-Analysis Approach
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