Yuanfeng Han

Carnegie Mellon University, Johns Hopkins University

Papers

8

Total Citations

123

H-Index

4

About

Yuanfeng Han is a roboticist whose work sits at the intersection of perception, manipulation, and physical reasoning for humanoid robots. His research focuses on enabling robots to understand and interact with the physical world through force sensing, tactile feedback, and learning-based estimation. In his most cited work, "The Curious Robot: Learning Visual Representations via Physical Interactions" (77 citations), Han pioneered methods for robots to learn about their environment not just by seeing, but by physically touching and manipulating objects—a foundational idea for embodied AI. He has made significant contributions to robot dexterity and autonomy, including developing force-sensing shoes and compliant gripping pads that allow smaller humanoid robots to sense ground reaction forces and grasp objects with precision. His work on reasoning about lifting feasibility addresses a critical gap in robotics: enabling robots to assess whether an action is physically possible before attempting it. Han also introduced a learning-based approach for estimating the inertial properties of unknown objects without expensive force/torque sensors, making such capabilities more accessible. Through these contributions, Han is advancing the next generation of physically intelligent robots that can safely and effectively operate in human environments.

Research Focus

Key Achievements

4
H-Index
8
Papers
123
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
The Curious Robot: Learning Visual Representations via Physical Interactions
77 citations · 2016
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Carnegie Mellon University, Johns Hopkins University

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago