
Wenbo Sun
Assistant Research Scientist
Location
University of Michigan Transportation Research Institute, 2901 Baxter Rd. Ann Arbor, MI 48109
Rm. 431
email: sunwbgt@umich.edu
Research Interests
Uncertainty quantification and decision making are increasingly demanded with the development of future technology in engineering and transportation systems. Among the uncertainty quantification problems, Dr. Wenbo Sun is particularly interested in statistical modeling of engineering system responses with considering the high dimensionality and complicated correlation structure, as well as quantifying the uncertainty from a variety of sources simultaneously, such as the inexactness of large-scale computer experiments, process variations, and measurement noises. He is also interested in data-driven decision making that is robust to the uncertainty. Specifically, he delivers methodologies for anomaly detection and system design optimization, which can be applied to manufacturing process monitoring, distracted driving detection, out-of-distribution object identification, vehicle safety design optimization, etc.
Biography
Wenbo Sun was most recently a postdoctoral research fellow at the Department of Industrial and Operations Engineering, at the University of Michigan College of Engineering. He obtained his Ph.D. degree from the same department under the supervision of Dr. Judy Jin and Dr. Matthew Plumlee in December 2018. His methodological research focuses on uncertainty quantification and decision making under uncertainty. He has been actively working on real-world problems in restraint system development, assistant driving system, precision health, and smart manufacturing.
Dr. Sun’s dissertation research focused on the methodologies for uncertainty quantification of functional responses, which have been applied to evaluate crash injury risk and improve vehicle design. During postdoctoral research, he has expanded this data analytics research to other application areas through joint projects with different units at the University of Michigan, including UMTRI, the Departments of Mechanical Engineering and Radiation Oncology. He has also worked on collaborative research projects with industry companies, including Honda R&D Americas, FCA, and Samsung. In these projects, he has developed statistical methods that are tailored to specific application problems. He has been lead author on eight journal articles based on this work, where his contributions included problem formulation, statistical modeling, mathematical derivation, coding solutions, and documentation. During his postdoctoral research, he has also developed and submitted four research proposals together with his advisor, Prof. Judy Jin, and other collaborators. One proposal was funded by the UM-Ford Alliance Program and additional proposals will be submitted to NSF. His research activities show an unusually high level of successful collaboration for a junior researcher. Appropriate to UMTRI’s mission, his work has focused on developing methods that have real-world impacts, based on a good understanding of the domain knowledge and the specific analytical needs. His independent work on statistical methodology development has enabled successes in diverse fields. For example, he worked in collaboration with the Department of Radiation Oncology on a precision health project that involved radiation dose determination and delivery. He designed a machine learning algorithm to adaptively adjust the radiation doses based on patients personal information. The work was demonstrated to have real-world impacts and led to a journal paper and a conference presentation.
Area of Expertise
Large scale computer experiments, uncertainty quantification, design optimization, statistical process control, deep neural network methodologies
Awards
- QCRE Best Student Paper Award, 2018 IISE Annual Conference
Service
Organizer and chair of technical sessions in Quality, Statistics and Reliability, INFORMS 2019-2021
Member in student organizer committee, MSSISS 2015-2016
Referee for journals: Technometrics, IISE Transaction, IEEE Transactions on Automation Sciences and Engineering, Computer in Industry
Additional Information
Hometown, Tianjin, China
Hobbies: badminton, baking, photography