Yifan Yin

I am a second-year Ph.D. student in Computer Science at Johns Hopkins University, advised by Professor Tianmin Shu.

Before my Ph.D., I completed my M.S.E. degree with a major in Robotics in the Laboratory for Computational Sensing and Robotics at Hopkins, under the supervision of Professor Russell Taylor and Professor Emad Boctor.

Email  /  CV  /  Twitter  /  Github

Research

My research is at the intersection of embodied AI, 3D vision, robotics, and human-robot interaction. My recent work focuses on (1) 3D world modeling for anticipating and evaluating embodied state changes; (3) robot learning via multimodal reasoning and experience reflection; and (4) integrated task and motion planning for embodied assistance and human-robot collaboration.

Publications

We present SIFToM, a neurosymbolic model that uses vision-language theory of mind to help robots follow noisy spoken instructions in collaborative settings.

We introduce PartInstruct, the first large-scale benchmark for training and evaluating fine-grained robot manipulation policies using part-level instructions.

We present a robust markerless image based visual servoing method that enables precision robot control without hand-eye and camera calibrations in 1, 3, and 5 degrees of freedom.

Service

• Workshop & Tutorial Organizers
  • RSS 2025 Workshop on Continual Robot Learning from Humans
• Reviewer
  • ICLR 2025 Workshop WRL
  • NeurIPS 2025 Workshop LAW

Media Coverage

• “Helping robots become a part of our world,” JHU WSE News, September 2025.