The Michigan Institute for Data & AI in Society (MIDAS) is proud to announce its 2026 cohort of Postdoctoral Affiliates, 10 outstanding researchers from diverse departments across the University of Michigan. This program is a key initiative in MIDAS’s mission to promote the development and application of AI and data science methodologies for scientific research throughout the university’s broader postdoctoral community.
The full list of 2026 MIDAS Postdoctoral Affiliates, including their disciplines, faculty mentors, and research themes, is:
Botton row, left to right: Rene Mai, Marvin Poul, Nizhum Rahman, Dimitrios Simatos, Tong Suo, Wenxin Yang, Yujing Yang
Eva Albalghiti
Ph.D., Environmental Engineering
MIDAS Postdoctoral Affiliate
Mentor: Brian Ellis, Civil and Environmental Engineering
Research Theme: AI/ML for making sense of complex geologic datasets
Youngheun Jo
Ph.D., Psychological and Brain Sciences; Cognitive Science
MIDAS Postdoctoral Affiliate
Mentor: Alexander Weigard, Psychiatry
Research Theme: Dynamic networks in brain development
Youran Lee
Ph.D., Nursing Science
MIDAS Postdoctoral Affiliate
Mentor: Ivo Dinov, School of Nursing
Research Theme: Large language models for multimodal EHR analysis
Rene Mai
Ph.D., Mechanical Engineering
MIDAS Postdoctoral Affiliate
Mentor: Dawn Tilbury, Mechanical Engineering; Lionel Roberts, School of Information
Research Theme: Data-driven analysis of human-robot teaming
Marvin Poul
Ph.D., Mechanical Engineering
MIDAS Postdoctoral Affiliate
Mentor: Thomas D. Swinburne, Mechanical Engineering
Research Theme: ML Models for Alloy Thermodynamics
Nizhum Rahman
Ph.D., Applied Mathematics
MIDAS Postdoctoral Affiliate
Mentor: Trachette L. Jackson, Mathematics
Research Theme: Data-Driven Modeling of Biomedical Systems
Dimitrios Simatos
Ph.D., Physics
MIDAS Postdoctoral Affiliate
Mentor: Venkat Viswanathan, Aerospace Engineering
Research Theme: Data-driven materials discovery
Tong Suo
Ph.D., Social Psychology
MIDAS Postdoctoral Affiliate
Mentor: Richard Gonzalez, Psychology
Research Theme: Data-driven modeling for psychological and economic well-being
Wenxin Yang
Ph.D., Geography
MIDAS Postdoctoral Affiliate
Mentor: Lauren E. Gillespie, School for Environment and Sustainability
Research Theme: Spatial Data Science for 3D Landscape Ecology and Biodiversity Conservation
Yujing Yang
Ph.D., Industrial Engineering
MIDAS Postdoctoral Affiliate
Mentor: Chenhui Shao, Mechanical Engineering
Research Theme: Perception-Driven Manufacturing Intelligence
A Thriving Interdisciplinary Community
Postdoctoral Affiliates are active members of the MIDAS postdoc community, joining a network of over 750 faculty affiliates and around 40 postdoctoral fellows. To foster this connection, affiliates attend talks, training activities, and collaborative meetings alongside the Michigan Data Science Fellows and the the Eric and Wendy Schmidt AI in Science Postdoctoral Fellows and African Faculty Fellows.
“The Postdoctoral Affiliates program is a vital part of our efforts to empower researchers across the entire University of Michigan campus,” said Jing Liu, Executive Director of MIDAS. “By providing these talented individuals with specialized resources and a collaborative interdisciplinary home, we are ensuring that cutting-edge AI and data science methodologies continue to catalyze innovation and drive discovery in every field of study.”
Opportunities for Growth and Collaboration
As part of their affiliation, these researchers participate in 2-4 hours of MIDAS activities weekly, gaining access to a robust suite of resources designed to accelerate their careers:
- Professional Development: Affiliates benefit from professional development workshops on topics including increasing research productivity, navigating academic and industry job searches, grantsmanship, and lab management.
- Weekly Research Meetings: These meetings allow postdocs and faculty to discuss ongoing projects, seek feedback, and build networks.
- Technical Training: Affiliates can attend all MIDAS training events and technical workshops at no cost, staying at the forefront of rapidly evolving AI tools.
- Faculty Connection Opportunities: The program provides formal and informal points of contact with the vast MIDAS faculty affiliate community, opening doors to new collaborations and career pathways.
- Research Collaboration through AI Carpentries: Affiliates are encouraged to join or start AI Carpentries—small, informal working groups focused on shared interests such as Large Language Models (LLMs), Reproducible AI Research, and Multi-Modal AI.
For more information about the Postdoctoral Affiliates Program, please visit our program page. The call for applications for the 2027 cohort is expected to be published in early 2027.