Postdoc Accomplishments

News / Postdoc Accomplishments

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 ...

News / Postdoc Accomplishments

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 ...

News / Postdoc Accomplishments

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, ...

News / Postdoc Accomplishments

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. ...

Postdoc Accomplishments / Research Impacts

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 ...

News / Postdoc Accomplishments

AI meets electrocatalysis: Lessons from three decades and a roadmap ahead

News / Postdoc Accomplishments

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 ...

Postdoc Accomplishments

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. ...

Postdoc Accomplishments

Optimizing Scientific Computing with Program Synthesis

Author: Zheng Guo Engineering Research Schmidt AI in Science Fellow Zheng Guo leverages program synthesis to accelerate scientific computing, with a particular focus on optimizing high-dimensional tensor approximations and computational kernels used across computational science. By automating the search for optimal network structures and contraction orders under diverse optimization objectives, his research enhances the efficiency and accuracy ...