Michigan Institute for Data Science announces 2023 fellows
Written by Jennifer Lewis
The Michigan Institute for Data Science (MIDAS) announces two new cohorts of postdoctoral fellows. Eleven new fellows will join the Eric and Wendy Schmidt AI in Science Fellowship program in the fall and two new fellows will join the Michigan Data Science Fellowship program.
The AI in Science 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. The Data Science Fellows will work at the boundaries of data science methods and domain sciences in an intellectually vibrant environment, and develop collaborative relationships with the U-M data science community. Both Fellowship programs are components of MIDAS’ effort to catalyze the transformative use of Data Science in a wide range of disciplines to achieve lasting societal impact, through research, training, outreach and partnership. The new Fellows will join a close-knit postdoc community with collocated work space at MIDAS and a variety of structured collaborative learning activities.
“I am constantly amazed by their fantastic research, their enthusiasm to learn new skills together, and their effort to strengthen the data science and AI campus research community.” says Dr. H. V. Jagadish, Director of MIDAS. “In the past few years, our postdocs have collaborated with researchers from more than 30 U-M departments. They have also been developing research incubation activities and technical workshops for the campus community.”
The postdocs will offer an annual AI in Science and Engineering symposium in the spring. They will also offer summer academies on AI methods to enable science and engineering research. Researchers who would like to discuss their ideas with the postdocs at their regular meetings can contact Jen Lewis, postdoc program manager (jlolewis@umich.edu).
The 2023 postdoctoral fellows, with their discipline, affiliated department, faculty mentors, and their degree-granting institution are:
Ph.D., Nuclear Engineering
Schmidt AI in Science Fellow
AI Mentor: Majdi Radaideh, Alex Gorodetsky, Aerospace Engineering
Science Mentor: Brendan Kochunas, Nuclear Engineering and Radiological Science
Research Theme: AI management of nuclear reactors
PhD., Ecology and Evolutionary Biology
Schmidt AI in Science Fellow
AI Mentor: David Fouhey, Computer Science and Engineering
Science Mentor: Brian Weeks, Environment and Sustainability
Research Theme: ML models for avian evolution
Ph.D., Fluid Mechanics; Ph.D., Astrophysics
Schmidt AI in Science Fellow
AI Mentor: Xun Huan, Mechanical Engineering
Science Mentor: Sally Oey, Astronomy
Research Theme: Deep Learning for spectral analysis for distant galaxies
Dual Ph.D., Computer Science and Engineering and Ecology and Evolutionary Biology
Schmidt AI in Science Fellow
AI Mentor: Kevin Wood, Biophysics
Science Mentor: Luis Zaman, Complex Systems; Ecology and Evolutionary Biology
Research Theme: Digital Evolution
Ph.D., Management
Data Science Fellow
Science Mentor: Mariel Lavieri, Industrial and Operations Engineering
Research Theme: Using AI methods to improve optimization algorithms and incorporating personal and organizational constraints for healthcare management decision making
Ph.D., Physics
Schmidt AI in Science Fellow
AI Mentor: Camille Avestruz, Physics
Science Mentor: Hsing-Wen Lin, Physics
Research Theme: Computer Vision Detecting the faintest objects in the Solar System
Ph.D., Civil Engineering
Schmidt AI in Science Fellow
AI Mentor: Lu Wang, Computer Science and Engineering
Science Mentor: Sabine Loos, Civil and Environmental Engineering
Research Theme: Analysis of city planning and infrastructure. Impact of and recovery from natural hazards
Ph.D., Environmental Engineering
Schmidt AI in Science Fellow
AI Mentor: Bryan Goldsmith, Chemical Engineering
Science Mentor: Mark Burns, Chemical Engineering
Research Theme: AI for sensor data analysis for water quality monitoring
Ph.D., Statistics and Social Data Analytics
Data Science Fellow
Science Mentor: Yajuan Si, Institute for Social Research
Research Theme: Refining formal privacy methods and applying them to survey data.
Ph.D., Aerospace Engineering
Schmidt AI in Science Fellow
AI Mentor: Katie Skinner, Robotics
Science Mentor: Dimitra Panagou, Aerospace Engineering
Research Theme: Intelligent visual and flow-based navigation for autonomous underwater vehicles
Ph.D., Environmental Studies
Shmidt AI in Science Fellow
AI Mentor: Yang Chen, Statistics
Science Mentor: Kai Zhu, Environment and Sustainability
Research Theme: Projecting nature’s calendar under climate change
Nanata Sophonrat
Ph.D., Materials Science and Engineering
Schmidt AI in Science Fellow
AI Mentor: Ambuj Tewari, Statistics
Science Mentor: Anne McNeil, Chemistry
Research Theme: Chemist in the loop ML for plastics recycling
Ph.D., Statistics
Shmidt AI in Science Fellow
AI Mentor: Yixin Wang, Statistics
Science Mentor: Bryan Goldsmith, Chemical Engineering
Research Theme: Causal reasoning in materials science
AI in Science Fellows appointed in 2022 who will continue fellowships include: 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.
Data Science Fellows appointed in 2022 who will continue fellowships are Bernardo Modenesi, Data Science and Elyse Thulin, Computational Methods to Better Understand Human Behaviors.
Fellowships are made possible by generous gifts from Schmidt Futures and the Rocket Companies. The call for applications for the 2024 cohort will be published in August, 2023.
For more information about the AI in Science Fellowship, please visit our program page.
For more information about the Data Science Fellowship, please visit our training page.