Master of Science in Robotics
Carnegie Mellon University, Class of 2023


Hello! My name is Dingkun Guo. I am a Master’s student in the Robotics Institute at Carnegie Mellon University. I am advised by Prof. Jeffrey Ichnowski and Prof. Chris Atkeson and working on manipulation, robot learning, and computer vision.

During my undergraduate at the University of Michigan, I was advised by Prof. Kenn Oldham. We created a small-scale walking-to-rolling robot. I was also advised by Prof. Xun Huan, and worked on uncertainty quantification of medical imaging AI.


Kitchen Robot Case Studies: Learning Manipulation Tasks from Human Video Demonstrations

Time: 12/5 3:30 pm
Location: GHC 8102

Leg Shaping and Event-Driven Control of a Small-Scale, Low-DoF, Two-Mode Robot

  • IEEE/ASME Transactions on Mechatronics, May 2022
  • IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), July 2022

Dingkun Guo, Larissa Wermers, Kenn R. Oldham

[website] [paper] [code] [presentation]

Lowering The Computational Barrier: Partially Bayesian Neural Networks for Transparency in Medical Imaging AI

  • Frontiers in Computer Science, Jan 2023 [paper]
  • SIAM Conference on Computational Science and Engineering, Feb 2023 [abstract]
  • SIAM Conference on Uncertainty Quantification, April 2022 [abstract]

Snehal Prabhudesai, Jeremiah Hauth, Dingkun Guo, Arvind Rao, Nikola Banovic, and Xun Huan

robot pouring water