Xiaojuan Qi

University of Hong Kong, University of Calgary

Papers

3

Total Citations

17

H-Index

2

About

Xiaojuan Qi is an emerging researcher at the intersection of robotics, human-robot interaction, and imitation learning, with a particular focus on advancing dexterous teleoperation systems. Her most notable contribution, **Bunny-VisionPro**, represents a significant leap forward in bimanual robotic control, addressing one of the field's most persistent challenges: enabling two robotic hands to coordinate seamlessly for complex, fine-grained manipulation tasks. By leveraging real-time teleoperation for human demonstration collection, her work provides a critical pipeline for training robots through imitation learning — a methodology increasingly central to modern robotics research. Bunny-VisionPro has rapidly gained recognition, accumulating over a dozen citations within its first year of publication, signaling strong community interest. Earlier in her career, Qi contributed to sensor evaluation research, examining the accuracy of time-of-flight cameras — including the Mesa Imaging SR4000 and Microsoft Kinect 2.0 — for structural monitoring applications, demonstrating a versatile technical foundation spanning both hardware sensing and advanced robotic systems. Her trajectory reflects a researcher steadily building toward high-impact solutions at the frontier of embodied AI and robot learning.

Research Focus

Key Achievements

2
H-Index
3
Papers
17
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Bunny-VisionPro: Real-Time Bimanual Dexterous Teleoperation for Imitation Learning
11 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: University of Hong Kong, University of Calgary

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago