LSTM-Based Anomalous Behavior Detection in Multi-Agent Reinforcement Learning. - Cameron Lischke; Tongtong Liu 001; Joe McCalmon; Md Asifur Rahman; Talal Halabi; Sarra M. Alqahtani (CSR, 2022)

Weaponizing Actions in Multi-Agent Reinforcement Learning: Theoretical and Empirical Study on Security and Robustness. - Tongtong Liu 001; Joe McCalmon; Md Asifur Rahman; Cameron Lischke; Talal Halabi; Sarra M. Alqahtani (PRIMA, 2022)

Task-Agnostic Safety for Reinforcement Learning. - Md Asifur Rahman; Sarra M. Alqahtani (AISec@CCS, 2023)

Adversarial Behavior Exclusion for Safe Reinforcement Learning. - Md Asifur Rahman; Tongtong Liu 001; Sarra M. Alqahtani (IJCAI, 2023)

A novel policy-graph approach with natural language and counterfactual abstractions for explaining reinforcement learning agents. - Tongtong Liu 001; Joe McCalmon; Thai Le; Md Asifur Rahman; Dongwon Lee 001; Sarra M. Alqahtani (Auton. Agents Multi Agent Syst., 2023)

Study of Partial Discharge Characteristics of Optimally Fabricated MMEI Flat Samples Under DC and Their DC Dielectric Strength for Applications in Envisaged All-Electric Wide-Body Aircraft. - Saikat Chowdhury; Anoy Saha; Md Asifur Rahman; Sai Pavan Kalakonda; Mona Ghassemi (IEEE Access, 2024)

xSRL: Safety-Aware Explainable Reinforcement Learning - Safety as a Product of Explainability. - Risal Shahriar Shefin; Md Asifur Rahman; Thai Le; Sarra Alqahtani (AAMAS, 2025)