Ruiqi Wang

Ruiqi Wang

R7 On the Beat

Ruiqi Wang

Hello!

I’m a Ph.D. candidate at Purdue University, where I work in the Smart Machine And Robotics Technology (SMART) Lab with Professor Byung-Cheol Min.

I am passionate about facilitating the seamless integration of robots into unstructured, human-centered environments: from assistive service in homes to collaborative operations in the field.

To this end, my research centers on developing Adaptive Human–Robot Systems that learn from and adapt to human-centered dynamics across three key dimensions:

  • Capability Heterogeneity: How to optimize human–robot teaming by accounting for inherent yet diverse human capabilities (e.g., cognitive abilities, skill levels, backgrounds) and robot characteristics (e.g., mobility, sensing, autonomy) within specific task contexts?
  • State Uncertainty: How to enable proactive perception and responsiveness to human states (e.g., cognitive load, attention, trust), robot working conditions, and task status that evolve dynamically during operation?
  • Preference Variability: How to align robot interactive patterns with individual preferences through continuous, multimodal human feedback?

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 Reinforcement Learning
  • Multi-Human Multi-Robot Teaming
  • Foundation Models for Robotics
  • Multimodal Perception and Reasoning

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