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About
Dr. Xiaoguang Dong received his Ph.D. degree from the Department of Mechanical Engineering (specialized in Robotics) at Carnegie Mellon University in 2019. He then worked as a postdoctoral researcher at the Max Planck Institute for Intelligent Systems, Stuttgart, Germany. Dr. Dong has long been working on the design, manufacture and control of microrobots for important applications such as biomedicine. His research works have been published in several top journals and conferences in the field of robotics, such as IEEE Transactions on Robotics, International Journal of Robotics Research, The IEEE International Conference on Robotics and Automation (ICRA), Robotics: Science and Systems (RSS). His interdisciplinary bioinspired robotics works have also been published in the top multidisciplinary journals such as Science Advances, PNAS and Nature Communications.
Institute Affiliation
The Vanderbilt Institute for Surgery and Engineering (VISE) is an interdisciplinary, trans-institutional entity designed to bring engineers and physicians together to impact healthcare.
Research Focus
Research at the Dong Lab includes designing the shape-morphing behaviors (single-body deformation and collective formations) in various soft matter to create functional miniature soft machines or minimally invasive medical devices, tightly integrated with their wireless actuation (e.g. magnetic), control and sensing systems, for biomedical, fluidics, and biomechanics applications. Ongoing research highlight includes developing novel minimally invasive medical functions of soft miniature robots, such as biofluid pumping and targeted biopsy. The long-term research of Dong Lab focuses on three aspects: 1) The design, manufacture and control of miniature soft robots, and their applications in minimally invasive medicine, microfluidics and biomechanics. 2) The design, manufacture and control of miniature swarm robots, and their applications in biomedicine and biomechanics. 3) The modeling, design, manufacture and control of intelligent soft materials and devices based on mechanics model and machine learning.
Education
Ph.D., Mechanical Engineering, Carnegie Mellon University
M.S., Mechanical Engineering, Carnegie Mellon University
B.S., Harbin Institute of Technology