At the forefront of AI-in-science innovation, MIDAS’s Schmidt AI in Science Postdoctoral Fellows are redefining the way artificial intelligence is applied across diverse research fields. Their cutting-edge research includes developing AI-driven techniques to uncover hidden patterns in complex genomic data, offering insights into large-scale biological processes like mass extinction events, developing methodologies for discovery and optimization of engineering processes and materials, and more. By bridging traditional research domains with AI-centric study, they enhance our ability to predict natural disasters, optimize aerospace engineering, and improve ecological monitoring. Their interdisciplinary collaborations and innovative solutions emphasize the potential of AI to drive scientific discovery and problem-solving.
ACT-Africa 2026 Concludes, Charts a Path for Contextual AI Innovation in Africa
The four-day ACT-Africa 2026 workshop, themed “Introduction to Foundation Models for Addressing African Community Challenges,” successfully concluded on September 9th at the Hyatt Regency Hotel in Addis Ababa . The landmark event brought together researchers, data scientists and developers from across the continent and the globe to tackle a critical challenge: adapting powerful AI technologies to … Read more
Spark Forum
Overview Research translation is not a final handoff. SPARK encourages participants to consider stakeholders, values, constraints, reproducibility, and adoption from the beginning of the research lifecycle—not only after the technical work is complete. The forum is being designed primarily for current and alumni Schmidt AI in Science Fellows from diverse scientific backgrounds and levels of … Read more
A Day in the Life of a MIDAS Postdoctoral Fellow
From CT-scanning leaves to exploring Michigan’s outdoors, Will Weaver‘s work as a MIDAS postdoctoral fellow bridges research, collaboration and discovery. A MIDAS postdoctoral fellowship is about more than conducting research. Fellows become part of a community of researchers working across disciplines, learning from one another and developing new approaches to some of today’s most challenging … Read more
MIDAS Postdoc Bootcamp 2026 – Welcoming the New Cohort
MIDAS is pleased to announce the arrival of the 2026 cohort of postdocs, including the Eric and Wendy Schmidt AI in Science Postdoctoral Fellows (AISP), the Eric and Wendy Schmidt African Faculty Fellows (AFF), and the Michigan Data Science (MDS) Fellows. They were joined by the 2026 cohort of the MIDAS Postdoctoral Affiliates (PA). Over … Read more
Announcing the 2026 cohort of Postdoctoral Affiliates
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 … Read more
AI tool reveals climate shifts may have fueled bursts of bird evolution
University of Michigan researchers used AI to uncover evidence that major climate shifts coincided with rapid bursts of bird evolution over the past 45 million years. Lead author Jacob Berv developed the novel statistical framework that enabled the team to analyze whole-skeleton data from thousands of bird species, revealing how climate change shaped the evolution … Read more
Commun-AI-ty Workshop Brings Researchers and Educators Together to Reimagine AI Science Communication
What if AI literacy weren’t developed in research labs alone, but co-designed with the communities it is intended to serve? That question brought together 54 participants from five countries for Commun-AI-ty: Building Science Communication Skills for Explaining AI in Science, a 3.5-day workshop held at the University of Michigan from June 23–26, 2026. Made possible … Read more
Large-Scale Evolution Simulations on PSC’s Neocortex Tackle Questions about Hypermutator Evolution
Matthew Andres Moreno, a Schmidt AI in Science Fellow, led groundbreaking research using the Pittsburgh Supercomputing Center’s Neocortex supercomputer to investigate why rapidly mutating organisms (“hypermutators”) rarely dominate in nature. By scaling evolutionary simulations from thousands to 1.5 billion virtual organisms, Moreno’s work uncovered how population size and the availability of beneficial mutations shape evolutionary … Read more
Data Visualization in R Workshop Helps Researchers Transform Data Into Publication-Ready Graphics
MIDAS African Faculty Fellow Dr. Verrah Otiende recently led a hands-on Data Visualization in R workshop for graduate students and postdocs, introducing participants to the R programming language and the ggplot2 visualization tool. The workshop brought together researchers with varying levels of coding experience to explore how raw research data can be transformed into clean, … Read more
U-M Uncertainty Quantification Incubator Brings Researchers Together to Advance Trustworthy AI
The Michigan Institute for Data and AI in Society (MIDAS) hosted the University of Michigan Uncertainty Quantification (UQ) Incubator from May 31 to June 3, 2026, bringing together researchers from a range of disciplines, including uncertainty quantification (UQ), artificial intelligence, science and engineering, to explore how AI systems can become more reliable, interpretable and trustworthy. … Read more
AI and Open Data Redesign Urban Transit: A Blueprint for Equity and Efficiency
Author: Yonas Minalu Emagnu, Schmidt Science African Faculty Fellow How do you design a public transport system for a city growing faster than its infrastructure? In two interconnected studies using Addis Ababa, Ethiopia as a case study, Dr. Yonas Minalu Emagnu, in collaboration with Tayo Fabusuyi, has developed a scalable, data-driven framework that answers this … Read more
Announcing the 2026 cohort of postdoctoral fellows
Michigan Institute for Data & AI in Society announces 2026 fellows Written by: Justin Varney The Michigan Institute for Data & AI in Society (MIDAS) is welcoming a new cohort of postdoctoral researchers and international faculty for 2026, further strengthening its global community that advances artificial intelligence and data science across disciplines. Eleven new postdoctoral … Read more
Bridging Knowledge and Experiment Gap with Differentiable Electrochemistry
Author: Haotian Chen Engineering Research Schmidt AI in Science Fellow Haotian Chen, along with his Science mentor Prof. Venkat Viswanathan and AI mentor Prof. Alexander Rodríguez are building the first differentiable electrochemistry framework to bridge the theory-experimental gap in electrochemistry. Electrochemistry simulations are made end-to-end differentiable to obtain gradients of physical processes for learning and optimization. … Read more