The Michigan Institute for Data Science (MIDAS) has welcomed its inaugural cohort of postdoctoral fellows as part of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship program. Made possible by a generous gift of more than $10 million from Schmidt Futures, the program aims to catalyze AI-enabled research breakthroughs in science and engineering and cultivate the next generation of research leaders. Over the course of six years, MIDAS plans to hire a total of 60 fellows for the program.
“The fellowship program is a valuable opportunity for postdoctoral researchers to advance knowledge in the era of big data and AI,” said H.V. Jagadish, Director of MIDAS and the Edgar F. Codd Distinguished University Professor of Electrical Engineering and Computer Science.
The 2022 postdoctoral fellows:
- James Boyko, Computational Methods, Microevolutionary Biology
- Yossi Cohen, Responsible AI, Industrial Decision-Making
- Nathan Fox, Crowdsourced data ML, Human Nature Interactions
- Jennifer Li, AI, Transient Sky
- Andreas Rauch, Data-Driven Modeling, Computational Fluid Dynamics
- Soumi Tribedi, AI methods, Electronic Structure Issues in Chemistry
- Anastasia Visheratina, AI, Advanced Functional Materials & Devices
- Yutong Wang, Developing Machine Learning Theory, Scientific Engineering Applications
- Xin Xie, AI in Topological Photonics
The fellows will not only work on their individual research projects but will also collaborate on initiatives to support the adoption of AI methods in science and engineering research in the U-M research community. This includes the upcoming AI in Science and Engineering Day to showcase AI-enabled science and engineering research and encourage cross-disciplinary collaboration.
Having a centralized “program home” at MIDAS offers the possibility of building a close-knit postdoc community. The fellows will engage in collaborative learning activities such as an AI Boot Camp, a three-day session that includes tutorials on AI skills and mentoring from faculty. The postdocs also formed AI Carpentries, small groups that focus on learning and collaboration around specific themes, such as: Hands-on Machine Learning in Python; Deep Learning; Causal Inference and explainable AI; Uncertainties quantification and Bayesian statistics. Attendees of the AI in Science and Engineering Day will learn about the Carpentries and how they facilitate collaboration.
MIDAS is a leader among academic data science institutes to promote ethical data and AI, which offers the postdoc program a unique feature. Dr. Jagadish notes, “Our program’s emphasis on ethical and responsible data and AI science is essential for ensuring that AI is used to advance scientific discovery in a way that benefits society as a whole.”
For more information, please visit our program page.