Laboratory for Intelligent Decision and Autonomous Robots (LIDAR)


Education

  • Postdoc Fellow, Harvard University, 2017-2018
  • Ph.D., The University of Texas at Austin, 2016
  • M.S., The University of Texas at Austin, 2013
  • B.S., Harbin Institute of Technology, 2011

Teaching Interests

Professor Zhao’s teaching interests encompass core mechanical engineering subjects, including dynamics, control systems, and robotics, at both undergraduate and graduate levels. He emphasizes the integration of fundamental principles with practical applications to prepare students for advanced study and professional practice. His teaching approach encourages active student participation and interdisciplinary learning to foster a comprehensive understanding of complex engineering systems. His courses aim to develop analytical and problem-solving skills essential to mechanical engineering.

Research Interests

Professor Zhao’s research focuses on robotics and autonomous systems, particularly on developing control and learning algorithms, sensing strategies, and system integration techniques. His work addresses challenges in manipulation, locomotion, and navigation for complex robotic systems such as locomotion and manipulation. The research aims to advance the adaptability and intelligence of robots through innovative methodologies in control theory, perception, and machine learning. Graduate and undergraduate students are actively involved in experimental, computational, and theoretical aspects of his research projects.

Recent Publications

  • EmoBipedNav: Emotion-aware Social Navigation for Bipedal Robots with Deep Reinforcement Learning. Wei Zhu, Abirath Raju, Abdulaziz Shamsah, Anqi Wu, Seth Hutchinson, Ye Zhao IEEE/ASME Transactions on Mechatronics, 2026
  • STATE-NAV: Stability-Aware Traversability Estimation for Bipedal Navigation on Rough Terrain Ziwon Yoon, Lawrence Y Zhu, Jingxi Lu, Lu Gan, Ye Zhao IEEE Robotics and Automation Letters, 2025
  • Opt2Skill: Imitating Dynamically-feasible Whole-Body Trajectories for Versatile Humanoid Loco-Manipulation Fukang Liu, Zhaoyuan Gu, Yilin Cai, Ziyi Zhou, Hyunyoung Jung, Jaehwi Jang, Shijie Zhao, Sehoon Ha, Yue Chen, Danfei Xu, Ye Zhao IEEE Robotics and Automation Letters, 10, 12261-12268, 2025
  • Learn to Teach: Sample-Efficient Privileged Learning for Humanoid Locomotion over Diverse Terrains Feiyang Wu, Xavier Nal, Jaehwi Jang, Wei Zhu, Zhaoyuan Gu, Anqi Wu, Ye Zhao IEEE Robotics and Automation Letters, 10, 9048-9055, 2025
  • Robust-Locomotion-by-Logic: Perturbation-Resilient Bipedal Locomotion via Signal Temporal Logic Guided Model Predictive Control Zhaoyuan Gu, Yuntian Zhao, Yipu Chen, Rongming Guo, Jennifer K. Leestma, Gregory S. Sawicki, Ye Zhao. IEEE Transactions on Robotics, 41, 4300-4321, 2025