Yaozhang Pan

About

Yaozhang Pan is a pioneering researcher at the intersection of neural rehabilitation and human-robot interaction (HRI). His most impactful work investigates how brain-computer interfaces (BCIs) and robotic training can restore motor function after stroke. In his landmark 2012 study, cited over 260 times, Pan used resting-state fMRI to reveal that changes in functional connectivity correlate with movement recovery following robot-assisted upper-extremity training. This work provided a crucial physiological predictor for rehabilitation outcomes, offering a window into how the brain rewires itself during therapy. Beyond neural rehabilitation, Pan has advanced the sensory capabilities of social robots. He developed intelligent vision systems for real-time face detection and audio systems for sound source recognition, both designed to help robots identify and interact with humans in cluttered environments. His later work on motor imagery BCIs and the fusion of CSP-derived features with time-domain parameters further refined mind-controlled robotic systems. By bridging neuroimaging, machine learning, and robotics, Pan’s research continues to shape the future of assistive technology and human-robot collaboration.

Research Focus

Key Achievements

Top Papers

1. 1
   Resting State Changes in Functional Connectivity Correlate With Movement Recovery for BCI and Robot-Assisted Upper-Extremity Training After Stroke

   263 citations · 2012
2. 2
   Real-time face detection for human robot interaction

   10 citations · 2009
3. 3
   Sound source recognition for human robot interaction

   4 citations · 2008
4. 4
   Mind Robotic Rehabilitation Based on Motor Imagery Brain Computer Interface

   3 citations · 2010
5. 5
   Fusion of CSP-derived features and Time-Domain Parameters for mind robotics control

   2 citations · 2011

Key Collaborators

Contact & Links