Yue Cao

Assistant Teaching Professor



Areas of Expertise:

  • Robotics 
  • Artificial Intelligence 

Yue Cao’s research centers on utilizing AI techniques to facilitate the automation and intelligence of robotic systems, particularly manipulators. His primary research goal is to advance task-oriented programming systems for manipulators. He focuses on developing approaches that integrate generative AI with classical robotics theory to achieve automatic task planning and planning-to-execution transition for manipulators. 

Honors and Awards: 

  • Magoon Excellence in Teaching Award, Purdue University, 2019 
  • Teaching Academy Graduate Teaching Award, Purdue University, 2023 

Selected Publications:  

Yue Cao and C. S. George Lee, “Behavior-Tree Embeddings for Robot Task-Level Knowledge,” IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022. 

Yue Cao and C. S. George Lee, “Robot Behavior-Tree-Based Task Generation with Large Language Models,” AAAI Spring Symposium Series, 2023. 

Yue Cao and C. S. George Lee, “Ground Manipulator Primitive Tasks to Executable Actions using Large Language Models,” AAAI Fall Symposium Series, 2023.