Min An
Papers
1
Total Citations
10
H-Index
1
About
Min An is a researcher in robotics and human-robot interaction, with a focus on enabling humanoid robots to learn natural, adaptive behaviors from human demonstration. Her key contribution lies in addressing the fundamental challenge of how robots can acquire the underlying behavioral criteria—rather than simply mimicking surface actions—to produce more fluid and intuitive motion. In her influential 2007 study, which has garnered 10 citations, An demonstrated that by prioritizing learning efficiency, robots can internalize the principles behind human movement, moving beyond rigid, pre-programmed routines that often appear unnatural. This work has implications for the development of more responsive and socially acceptable robotic assistants. An’s research bridges machine learning, cognitive science, and robotics, offering a pathway toward robots that not only perform tasks but do so in ways that feel familiar and comfortable to human collaborators. Her approach continues to inform efforts in adaptive manipulation and autonomous skill acquisition.
Research Focus
Key Achievements
Top Papers
- 1