Publications

2022
Esmaeil Seraj, Zheyuan Wang, Rohan Paleja*, Daniel Martin, Matthew Sklar, and Matthew Gombolay
Learning Efficient Diverse Communication for Cooperative Heterogeneous Teaming
In Proc. Autonomous Agents and Multiagent Systems (AAMAS). [38% Acceptance Rate]
Rohan Paleja
Mutual Understanding in Human-Machine Teaming
Accepted to the AAAI-22 Doctoral Consortium
2021
Rohan Paleja, Muyleng Ghuy, Nadun Ranawaka, Reed Jensen, and Matthew Gombolay
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming  
In Proc. Conference on Neural Information Processing Systems (NeurIPS). [26% Acceptance Rate]
Roger Dias, Marco Zenati, Geoff Rance, Rithy Srey, David Arney, Letian Chen, Rohan Paleja, Lauren Kennedy-Metz, and Matthew Gombolay
Using Machine Learning to Predict Perfusionists’ Critical Decision-Making during Cardiac Surgery
In. Computer Methods in Biomechanics and Biomedical Engineering.
Yaru Niu*, Rohan Paleja*, and Matthew Gombolay
MAGIC: Multi-Agent Graph-Attention Communication 
In Proc. ICCV 2021 Workshop on Multi-Agent Interaction and Relational Reasoning. [Spotlight Talk] [Best Paper Award]
Letian Chen, Rohan Paleja, and Matthew Gombolay
Towards Sample-efficient Apprenticeship Learning from Suboptimal Demonstration 
In Proc. AAAI Artificial Intelligence for Human-Robot Interaction (AI-HRI) Fall Symposium.
Rohan Paleja, Andrew Silva, Letian Chen, and Matthew Gombolay
Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User Demonstrations
In Proc. AAMAS Autonomous Robots and Multirobot Systems (ARMS) Workshop.
Mariah Schrum*, Glen Neville*, Michael Johnson*, Nina Moorman, Rohan Paleja, Karen Feigh, and Matthew Gombolay
Effects of Social Factors and Team Dynamics on Adoption of Collaborative Robot Autonomy
In Proc. International Conference on Human-Robot Interaction (HRI). [23% Acceptance Rate]
Yaru Niu*, Rohan Paleja*, and Matthew Gombolay
Multi-Agent Graph-Attention Communication and Teaming
In Proc. Autonomous Agents and Multiagent Systems (AAMAS). [25% Acceptance Rate]
2020
Letian Chen, Rohan Paleja, and Matthew Gombolay
Learning from Suboptimal Demonstration via Self-Supervised Reward Regression 
In Proc. Conference on Robot Learning (CoRL). [34% Acceptance Rate] [Plenary Talk] [Best Paper Finalist]
Rohan Paleja, Andrew Silva, Letian Chen, and Matthew Gombolay
Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User Demonstrations 
In Proc. Conference on Neural Information Processing Systems (NeurIPS). [20% Acceptance Rate]
Letian Chen, Rohan Paleja, Muyleng Ghuy, and Matthew C. Gombolay
Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation
In Proc. International Conference on Human-Robot Interaction (HRI). [24% Acceptance Rate]
2019
Rohan Paleja and Matthew C. Gombolay
Heterogeneous Learning from Demonstration     
In Proc. International Conference on Human Robot Interaction (HRI) Pioneers Workshop. [32% Acceptance Rate]