Brian Do

Portrait of Brian Do.

Brian Do

Assistant Professor
Collaborative Robotics and Intelligent Systems Institute
Mechanical, Industrial, and Manufacturing Engineering

Corvallis, OR 97331
United States

Ph.D., Mechanical Engineering, Stanford University, 2023
M.S., Mechanical Engineering, Stanford University, 2019
B.S., Mechanical Engineering, Georgia Institute of Technology, 2017

Brian H. Do is an Assistant Professor in the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University. He received his Ph.D. and M.S. degrees from Stanford University and his B.S. from the Georgia Institute of Technology, all in mechanical engineering. He completed his doctoral work in the CHARM Lab and was a postdoctoral scholar in the Yale University Faboratory.

Dr. Do aims to create human-centered robots capable of adapting to and interacting with the physical world. His research focuses on the design and modeling of robots that adapt their morphology and mechanical properties for use in exploration, navigation, manipulation, and haptics.

He has been named a Trailblazer in Engineering and an RSS Pioneer. He was awarded the Stanford School of Engineering Justice, Equity, Diversity, and Inclusion Graduation Award for his excellence in mentorship and outreach.

Research Interests
Dr. Do’s research interests include soft robotics, growing robots, variable stiffness systems, robot design and modeling, bioinspired systems, haptics, and physical human-robot interaction.

Selected Publications

  • B. H. Do, S. Wu, R. Zhao, and A. M. Okamura. (Submitted). Stiffness Change for Reconfiguration of Inflated Beam Robots. doi: arXiv:2307.03247 [cs.RO]
  • B. H. Do, I. Choi, and S. Follmer. (2022). An All-Soft Variable Impedance Actuator Enabled by Embedded Layer Jamming. IEEE/ASME Transactions on Mechatronics. doi: 10.1109/TMECH.2022.3183576
  • O. G. Osele, A. M. Okamura, and B. H. Do. (2022). A Lightweight, High-Extension, Planar 3-Degree-of-Freedom Manipulator Using Pinched Bistable Tapes. IEEE International Conference on Robotics and Automation, pp. 1190-1196, doi: 10.1109/ICRA46639.2022.9811976.