Call for Participation - Uncertainty Quantification (UQ) Incubator Workshop, University of Michigan
Zheng Guo
Uncertainty Quantification (UQ) Incubator:
Building Trustworthy AI for Science and Engineering
Date: May 31 to June 3, 2026
Location: The University of Michigan, Ann Arbor
Website: https://midas.umich.edu/events/uq-incubator-2026/
Submit your application by March 31!
Application: https://forms.gle/Y4ubKDQxAv6tQVyY6
Overview:
The UQ Incubator is a launchpad for cross-disciplinary innovation around Uncertainty Quantification (UQ) in AI for Science and Engineering. We aim to bring together two critical communities: UQ experts, who develop rigorous mathematical methods, and domain scientists/engineers, who apply AI to complex problems in science and engineering. We will provide you with a structured collaborative environment where UQ experts can access real-world scientific datasets, and scientists can acquire the “UQ toolbox” needed to make their AI models trustworthy. This event is supported by Schmidt Sciences, a private philanthropic organization.
Program Highlights:
Knowledge Building: Keynote lectures and interactive tutorials designed to build a shared language between UQ experts and domain scientists.
Collaborative Prototyping: The research sprint is structured in two phases:
The Match: Structured speed-networking and poster sessions help you form long-lasting collaborations among scientists/engineers with data and UQ experts with solid methods.
The Sprint: Once teams are formed, the clock starts. You will have 24 hours to “hack” a research question, moving from concept to preliminary prototype.
Seed Funding: At the end of the sprint, teams will pitch their research prototypes. Up to 10 teams will be awarded $2,500 research grants to fund post-event travel and publications.
Keynote Speakers:
Dr. Michael Shields: Professor, Civil & Systems Engineering, Johns Hopkins University
Dr. Douglas Allaire: Associate Professor, Mechanical Engineering, Texas A&M University
Dr. Yang Chen: Associate Professor of Statistics, University of Michigan
Attendees:
The workshop is open to the public. Local expenses are fully covered and limited travel awards are available. Ideal attendees include postdoctoral researchers, early-career faculty members, and senior PhD students who are:
Domain Scientists/Engineers seeking to make their AI-driven research more robust and interpretable, with strong research interests in applying rigorous UQ analysis and algorithms to scientific and engineering problems, including but not limited to biology, chemistry, physics, climate, environmental science, engineering and computer science.
UQ Experts looking for high-impact, real-world problems to drive their methodological research, who are enthusiastic about integrating domain knowledge, including equations, process-based models, and theory, into machine learning and statistics.
Next Steps:
Check for more information at https://midas.umich.edu/events/uq-incubator-2026/ and contact us at uqinc...@umich.edu if you have more questions!
Best regards,
The UQ Incubator Team
Research Fellow
Michigan Institute for Data & AI in Society