Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach. - James Queeney; Ioannis Ch. Paschalidis; Christos G. Cassandras (AAAI, 2021)

Generalized Proximal Policy Optimization with Sample Reuse. - James Queeney; Yannis Paschalidis; Christos G. Cassandras (NeurIPS, 2021)

Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning. - James Queeney; Mouhacine Benosman (NeurIPS, 2023)

A Model-Based Approach for Improving Reinforcement Learning Efficiency Leveraging Expert Observations. - Erhan Can Ozcan; Vittorio Giammarino; James Queeney; Ioannis Ch. Paschalidis (CDC, 2024)

Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees. - Yilei Chen; Vittorio Giammarino; James Queeney; Ioannis Ch. Paschalidis (CoRR, 2024)

Visually Robust Adversarial Imitation Learning from Videos with Contrastive Learning. - Vittorio Giammarino; James Queeney; Ioannis Ch. Paschalidis (CoRR, 2024)

GRAM: Generalization in Deep RL with a Robust Adaptation Module. - James Queeney; Xiaoyi Cai; Mouhacine Benosman; Jonathan P. How (CoRR, 2024)

Adversarial Imitation Learning from Visual Observations using Latent Information. - Vittorio Giammarino; James Queeney; Ioannis Ch. Paschalidis (Trans. Mach. Learn. Res., 2024)

Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees. - James Queeney; Erhan Can Ozcan; Ioannis Ch. Paschalidis; Christos G. Cassandras (Trans. Mach. Learn. Res., 2024)

Generalized Policy Improvement Algorithms With Theoretically Supported Sample Reuse. - James Queeney; Ioannis Ch. Paschalidis; Christos G. Cassandras (IEEE Trans. Autom. Control., 2025)

PIETRA: Physics-Informed Evidential Learning for Traversing Out-of-Distribution Terrain. - Xiaoyi Cai; James Queeney; Tong Xu; Aniket Datar; Chenhui Pan; Max Miller; Ashton Flather; Philip R. Osteen; Nicholas Roy; Xuesu Xiao; Jonathan P. How (IEEE Robotics Autom. Lett., 2025)