Welcome to the webpage of Human-Centered AI and Robotics (HCAIR) Group! We are part of the Department of Computer Science at Rice University, and are located in Anne and Charles Duncan Hall at the George R. Brown School of Engineering.

We envision a future where AI systems support humans as assistants, teammates, and even trainers. We are interested in developing computational foundations of these interactive AI systems that enhance human capability. To develop these foundations, our research methodology involves developing machine learning and decision-making algorithms, prototyping them on interactive AI systems (such as robots and recommender systems), and evaluating them with human users.

We believe that to arrive at the computational foundations of interactive AI systems, it is essential to adopt a cross-disciplinary perspective and ground research in both near-term and futuristic applications. In our ongoing work, we are exploring applications of Human-AI Collaboration in healthcare and disaster response. We are fortunate to have collaborators with deep expertise in psychology, physiological sensing, team science and medicine. By merging our computational contributions with domain expertise of our collaborators, we are developing solutions to model human behavior, train teams of humans and robots, and explain behavior of AI systems.

Director: Vaibhav Unhelkar, Assistant Professor of Computer Science, Rice University

Research Areas: Human-Robot Interaction, Interactive Machine Learning, and Explainable AI.

Selected Publications

  1. Automated Task-Time Interventions to Improve Teamwork using Imitation Learning
    Sangwon Seo, Bing Han, and Vaibhav Unhelkar
    In International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), May 2023
  2. Semi-Supervised Imitation Learning of Team Policies from Suboptimal Demonstrations
    Sangwon Seo, and Vaibhav Unhelkar
    In International Joint Conference on Artificial Intelligence (IJCAI), Jul 2022
  3. Evaluating the Role of Interactivity on Improving Transparency in Autonomous Agents
    Peizhu Qian, and Vaibhav V Unhelkar
    In International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), May 2022
  4. Human-Guided Motion Planning in Partially Observable Environments
    Carlos Quintero-Pena*, Constantinos Chamzas*, Zhanyi Sun, Vaibhav Unhelkar, and Lydia E Kavraki
    In International Conference on Robotics and Automation (ICRA), May 2022
  5. Towards an AI Coach to Infer Team Mental Model Alignment in Healthcare
    Sangwon Seo, Lauren R Kennedy-Metz, Marco A Zenati, Julie A Shah, Roger D Dias, and Vaibhav V Unhelkar
    In International Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA), May 2021