Ruiqi Wang (R7)
Hello!
I’m a Ph.D. candidate in the Smart Machine and Assistive Robotics Technology (SMART) Lab at Purdue University, advised by Professor Byung-Cheol Min.
My primary research centers on developing adaptive human-robot systems to facilitate the seamless integration of robots into daily human life. I mainly investigate adaptation mechanisms across three key dimensions:
- Team Heterogeneity: How to optimize human-robot teaming by accounting for inherent yet heterogeneous human capabilities (e.g., cognitive abilities, skill levels, backgrounds) and robot characteristics (e.g., mobility, sensory abilities, autonomy levels)?
- Operational Dynamics: How to enable proactive perception and adapt to evolving human states (e.g., cognitive load, fatigue), robot working conditions, and changing task requirements during operation?
- Individual Preferences: How to personalize robot interactive behaviors to individual preferences through human-in-the-loop learning?
Spanning scales from one-to-one human-robot interaction to team-level coordination in multi-human multi-robot teams, my work aims to lay the foundation for a future where robots can naturally understand, adapt to, and collaborate with any human, in any context or situation.
My broad areas of research include:
- Human-Robot Interaction
- Human-in-the-Loop Robot Learning
- Multi-Human Multi-Robot Teaming
- Multimodal Perception and Reasoning
- Affective Computing
- Foundation Models for Robotics
News
- 01/06/2025: Our paper “PrefCLM: Enhancing Preference-based Reinforcement Learning with Crowdsourced Large Language Models” has been accepted for publication in IEEE Robotics and Automation Letters (RA-L)!
- 12/16/2024: Arjun, an undergraduate I mentored, won First Place at the Purdue University 2024 Fall Undergraduate Research Expo! He presented his outstanding research on Initial Task Allocation in Multi-Human Multi-Robot Teams.
- 12/13/2024: I passed my Ph.D. dissertation proposal defense!
- 11/26/2024: Our paper “Cognitive Load-based Affective Workload Allocation for Multi-Human Multi-Robot Teams” has been accepted for publication in IEEE Transactions on Human-Machine Systems!
- 07/10/2024: Our paper “MOCAS: A Multimodal Dataset for Objective Cognitive Workload Assessment on Simultaneous Tasks” has been accepted for publication in IEEE Transactions on Affective Computing!
- 05/02/2024: I passed my Ph.D. preliminary exam! Special thanks to my advisor, my committee members, and my peers in the SMART lab!
- 02/05/2024: Our paper “Initial Task Assignment in Multi-Human Multi-Robot Teams: An Attention-enhanced Hierarchical Reinforcement Learning Approach” has been accepted for publication in IEEE Robotics and Automation Letters (RA-L)!
- 01/28/2024: Our paper “SAMARL: Multi Robot Socially-aware Navigation with Multi-agent Reinforcement Learning” has been accepted in ICRA 2024!
- 01/17/2024: Our paper “Husformer: A Multi-Modal Transformer for Multi-Modal Human State Recognition” has been accepted for publication in IEEE Transactions on Cognitive and Developmental Systems! Check out our source code as well!
- 12/28/2023: Conducted a one-day robotics seminar at West Lafayette Jr./Sr. High School to introduce and explore the realms of cutting-edge research in human-robot interaction, multi-robot systems, and robot design.
- 06/21/2023: Two papers “Initial Task Allocation for Multi-Human Multi-Robot Teams with Attention-based Deep Reinforcement Learning” and “NaviSTAR: Socially Aware Robot Navigation with Hybrid Spatio-Temporal Graph Transformer and Preference Learning” are accepted in IROS 2023!
- 05/27/2023: Conducted an exceptional five-day robotics outreach program at West Lafayette Jr./Sr. High School to captivate K-12 students with the intriguing world of robotics, providing them with invaluable hands-on experiences and insights into practical applications!
- 12/18/2022: Held a one-day outreach event at Macau Anglican College to provide K-12 students and their teachers with cutting-edge robotic research on Human-in-the-loop Reinforcement Learning and Affective Robotics!
- 06/30/2022: Our paper “Feedback-efficient Active Preference Learning for Socially Aware Robot Navigation” is accepted in IROS 2022! Check the Project Website for details.