Simulation-Acquired Latent Action Spaces for Dynamics Generalization. - Nicholas Corrado; Yuxiao Qu; Josiah P. Hanna (CoLLAs, 2022)

Deep Reinforcement Learning for Distribution Power System Cyber-Resilience via Distributed Energy Resource Control. - Nicholas E. Corrado; Michael Livesay; Tyson Bailey; Jay Johnson; Drew Levin (SmartGridComm, 2023)

On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling. - Nicholas E. Corrado; Josiah P. Hanna (CoRR, 2023)

Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates. - Nicholas Corrado; Josiah P. Hanna (ICLR, 2024)

Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning. - Nicholas E. Corrado; Yuxiao Qu; John U. Balis; Adam Labiosa; Josiah P. Hanna (RLJ, 2024)

AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs. - Nicholas E. Corrado; Julian Katz-Samuels; Adithya M. Devraj; Hyokun Yun; Chao Zhang; Yi Xu 011; Yi Pan; Bing Yin; Trishul Chilimbi (ACL (1), 2025)

When Can Model-Free Reinforcement Learning be Enough for Thinking? - Josiah P. Hanna; Nicholas E. Corrado (CoRR, 2025)