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Photo file: 
photograph of Ye Zhao
Full name: 
Ye Zhao
Job title: 
Assistant Professor
(ECE Adjunct)
Technical Interest Groups: Systems and Controls
Email address: 
Work phone: 
GTMI 437

Ye Zhao received the B.E. degree in Control Science and Engineering from Harbin Institute of Technology, China, in 2011 and the M.S. and Ph.D. degrees in mechanical engineering from The University of Texas at Austin in 2013 and 2016, respectively, where he also received the UT Robotics Graduate Portfolio Program degree. He received HIT Honor Undergraduate Thesis Award, and his co-authored work was recognized as the 2017 Thomson Reuters Highly Cited Paper and 2016 IEEE-RAS best whole-body control paper and video award finalist. Before joining Georgia Tech, he was a Postdoctoral Fellow at Computer Science, the John A. Paulson School of Engineering and Applied Sciences, Harvard University. Dr. Zhao started as an Assistant Professor at the George W. Woodruff School of Mechanical Engineering in January 2019. He directs the Laboratory for Intelligent Decision and Autonomous Robots (LIDAR) at Georgia Tech.

Dr. Zhao’s research interests lie broadly in planning, control, decision-making, applied optimization, and learning algorithms of highly dynamic, under-actuated, and human-cooperative robots maneuvering in dynamically-changing, unstructured, and possibly adversarial environments. He is especially interested in computationally efficient optimization algorithms and formal methods for challenging robotics problems with formal guarantees on robustness, safety, provable correctness, autonomy, and real-time performance. The LIDAR group he leads at Georgia Tech aims at pushing the boundary of robot autonomy, intelligent decision, robust motion representation, and symbolic planning reasoning.

Contact information:
The George W. Woodruff School of Mechanical Engineering
GTMI Office 437
Georgia Institute of Technology
813 Ferst Dr NW
Atlanta, GA, USA, 30332
E-mail: ye.zhao@me.gatech.edu
Telephone: +1 (404) 894-3061

Research interests: 
  • Legged locomotion and manipulation
  • Task and motion planning
  • Applied optimization
  • Decision-making
  • Formal methods

Y. Li, J. Warnke, and Y. Zhao. "Towards Safe Locomotion Navigation in Partially Observable Environments with Uneven Terrain." IEEE Conference on Decision and Control. 2020.

S. Kulgod, J. Huang, W. Chen, Y. Zhao, and N. Atanasov. "Temporal Logic Guided Locomotion Planning and Control in Cluttered Environments." American Control Conference. 2020.

Z. Zhou, and Y. Zhao. "Accelerated ADMM based Trajectory Optimization for Legged Locomotion with Coupled Rigid Body Dynamics." American Control Conference. 2020.

Y. Zhao, N. Paine, S. Jorgensen, and L. Sentis. "Impedance Control and Performance Measure of Series Elastic Actuators.” IEEE Transactions on Industrial Electronics, 2018, 65(3), 2817-2827.

Y. Zhao, B. Fernandez, and L. Sentis. "Robust Optimal Planning and Control of Non-Periodic Bipedal Locomotion.” International Journal of Robotics Research. 36(11): 1211-1243, September, 2017.

D. Kim, Y. Zhao, G. Thomas, B. Fernandez, and L. Sentis. "Stabilizing Series-Elastic Point-Foot Bipeds using Whole-Body Operational Space Control." IEEE Transactions on Robotics. 2016, 32(6): 1362-1379.

Y. Zhao, B. Fernandez, and L. Sentis. "Robust Phase-Space Planning for Agile Legged Locomotion over Various Terrain Topologies." Robotics: Science and Systems, 2016.

Y. Zhao, N. Paine, K. Kim, and L. Sentis. "Stability and Performance Limits of Latency-Prone Distributed Feedback Controllers." IEEE Transactions on Industrial Electronics. 2015, 62(11): 7151-7162.

Y. Zhao, L. Zhang, S. Shen, and H. Gao. "Robust Stability Criterion for Discrete-time Uncertain Markovian Jumping Neural Networks with Defective Statistics of Modes Transitions." IEEE Transactions on Neural Networks. 2011, 22(1): 164-170.

Last revised August 31, 2020