Xiaoli Zhang

Associate Professor, Mechanical Engineering

Xiaoli ZhangDr. Xiaoli Zhang’s research expertise lies in human-robot cooperation, knowledge-based robotics, intelligent control, teleoperation, and their applications in healthcare and industrial fields. Her research goal is to improve the flexibility, adaptability, and robustness of robots and autonomous systems so they can operate and adapt to deal with new problems and situations or deal with changes in tasks, environments, and human cooperators. Her work crosses different applications, including assistive robots, surgery, additive manufacturing, material discovery and underground construction, and draws from optimal control, planning, reasoning, learning and cognitive science. Dr. Zhang is a recipient of an NSF CAREER award.


Brown Hall 280D

Labs and Research Centers

Research Areas

  • Smart human-machine/robot interaction and cooperation, shared autonomy
  • Artificial-intelligence-powered automation and acceleration of engineering process optimization and science discovery, adaptive design of experiments
  • Efficient and robust machine learning for robots and autonomous systems

Recent Publications

View full list on Google Scholar


  • Liu, S., Stebner, A.P., Kappes, B.B., Zhang X. “Machine Learning for Knowledge Transfer Across Multiple Metals Additive Manufacturing Printers,” Additive Manufacturing, 39:101877 (2021).
  • Liu, S., Kappes, B.B., Amin-Ahmadi, B., Benafan, O., Zhang, X., Stebner A.P “Physics-informed machine learning for composition-process-property design: shape memory alloy demonstration,” Applied Materials Today, 22:100898 (2021).
  • Liu, R., Liu, S., Zhang, X. “A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing,” The International Journal of Advanced Manufacturing Technology, 113:1943–1958 (2021).
  • Luo, L., Tang, L., Liu, R., Zhang, X., Yang, Z.-X. “Multi-modality Learning for Non-rigid 3D Shape Retrieval via Structured Sparsity Regularizations,” IEEE Sensors Journal, doi: 10.1109/JSEN.2021.3094122.
  • Tao, L., Bowman, M., Zhang, J., Zhang, X. “Learn Task First or Learn Human Partner First: A Hierarchical Task Decomposition Method for Human-Robot Cooperation,” IEEE International Conference on Systems, Man, and Cybernetics, Oct. 17–20, Melbourne, Australia (2021).
  • Bowman, M., Zhang, X. “Dynamic Pre-Grasp Planning When Tracing a Moving Object through a Multi-Agent Perspective,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept. 27–Oct. 1, Prague, Czech Republic (2021).


  • Johnson N.S, Vulimiri, P.S., To, A.C., Zhang, X., Brice, C.A., Kappes, B.B., Stebner, A.P. “Machine learning for materials developments in metals additive manufacturing,” Additive Manufacturing, 36:101641 (2020).
  • Li, S., Bowman, M., Nobarani, H., Zhang, X., “Inference of Manipulation Intent in Teleoperation for Robotic Assistance.” Journal of Intelligent & Robotic Systems https://doi.org/10.1007/s10846-019-01125-8 (2020).


  • Zhou, X., Zhang, X. “Multi-Objective-Optimization Based Auto-Tuning of Control Parameters for Quadrotors Equipped with a Robotic Arm.” International Journal of Advanced Robotic Systems, 16(1):1–13 (2019).
  • Liu, R., Zhang, X. “Methodologies for Realizing Natural-Language-Based Human-Robot Cooperation: A Review.” International Journal of Advanced Robotic Systems, 16(3):1–17 (2019).


  • Liu, R., Zhang, X. “Generating Machine-Executable Plan from Human’s Natural Instructions.” Knowledge-Based Systems, 140:15–26 (2018).


  • Li, S., Zhang, X., Webb, J. “3D-Gaze-Based Robotic Grasping Through Mimicking Human Visuomotor Function for People with Motion Impairments.” IEEE Transactions on Biomedical Engineering 64(12):2824–2835 (2017).
  • Li, S., Zhang, X. “Implicit Intention Communication in Human-Robot Interaction Through Visual Behaviour Studies.” IEEE Transactions on Human-Machine Systems 47(4):437–448 (2017).
  • Li. S., Webb, J., Zhang, X., Nelson, C. A. “User Evaluation of a Novel Eye-Based Control Modality for Robot-Assisted Object Retrieval.” Advanced Robotics 31(7):382–393 (2017).


  • Liu R., Zhang X., Zhang, H. “Web-Video-Mining-Supported Workflow Modeling for Robotic Surgeries.” Artificial Intelligence in Medicine 74:9–20 (2016).
  • Liu, R., Zhang, X. “Context-Specific Grounding of Web Natural Descriptions to Human-Centered Situations.” Knowledge-Based Systems 111:1–16 (2016).
  • Liu, R., Zhang, X. “Fuzzy-Context-Specific Intention Inference for Robotic Caregiving.” International Journal of Advanced Robotic Systems 13(5):1729881416662780 (2016).

View full list on Google Scholar

Recent Courses

  • MEGN 545 Advanced Robot Control
  • MEGN 441 Introduction to Robotics