Conformal uncertainty sets for robust optimization. - Chancellor Johnstone; Bruce Cox (COPA, 2021)

Constructing Prediction Intervals with Neural Networks: An Empirical Evaluation of Bootstrapping and Conformal Inference Methods. - Alex Contarino; Christine M. Schubert-Kabban; Chancellor Johnstone; Fairul Mohd-Zaid (CoRR, 2022)

Exact and Approximate Conformal Inference in Multiple Dimensions. - Chancellor Johnstone; Eugène Ndiaye (CoRR, 2022)

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)

Multi-Objective Multi-Commodity Flow Optimization for Wartime Planning with Cyber-Effects. - Alex Hoffendahl; Chancellor Johnstone; Alex Stephens; Richard Dill; Lance E. Champagne (INOC, 2024)

H2G2-Net: A Hierarchical Heterogeneous Graph Generative Network Framework for Discovery of Multi-Modal Physiological Responses. - Haidong Gu; Nathan B. Gaw; Yinan Wang; Chancellor Johnstone; Christine Beauchene; Sophia Yuditskaya; Hrishikesh Rao 002; Chun-An Chou (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)

Exact and Approximate Conformal Inference for Multi-Output Regression. - Chancellor Johnstone; Eugène Ndiaye (COPA, 2025)