MIDAS Annual Highlights 2022

MIDAS strengthens University of Michigan’s preeminence in Data Science and Artificial Intelligence by catalyzing its transformative use across a wide range of research disciplines and building a world-class, inclusive community of researchers at U-M. MIDAS provides leadership and training in best practices as well as fosters interdisciplinary collaboration to achieve lasting, societal impact.

Letter from the Director

“I’d like to extend my gratitude and holiday greetings to the MIDAS affiliated faculty, U-M data science and AI researchers and students, and our 50+ community partnerships across higher education, government, industry, and nonprofit organizations. Thanks to your enduring effort, together, we continue to grow and drive forward the mission of using data science and AI research for scientific breakthroughs and positive social impact and change.”

Click to read full letter.

- H.V. Jagadish
MIDAS Director

Research Pillars

MIDAS focuses on research activities in five interconnected “pillars” with the goal of promoting best practices and encouraging the adoption of new data types and methodologies. These key areas include: 

  1. Responsible Research Pillar
  2. Data Pillar
  3. Analytics Pillar
  4. AI Pillar
  5. Emerging Pillar

We celebrate the achievements of the U-M data science and AI research community in 2022 and present these stories as a small sample of the multitude of ways in which our efforts support research, training, collaboration, and community.

Responsible Data Science and AI - Future Leaders Summit 2022
This annual event aims to build a network for students and postdoctoral fellows and nurture them to become the next generation of academic leaders in the field.
Propelling Original Data Science - 2022 Funded Projects
10 teams across U-M comprise the 2022 PODS Grants awardees, whose projects use data science and AI methodologies to study a wide range of subjects, including climate change, medicine, gender equity, and more.
Empowering New Research with Social Media Data
From pilot-funding University of Michigan faculty-led projects in the social sciences to an industry partnership with Twitter and use of their data-sets, MIDAS continues to provide resources for advancing research in social media.
MIDAS Challenge Grant Funding leads to Groundbreaking Ability to Study Single Cells using Data Science
Dr. Jun Li leads a multidisciplinary team at the Michigan Center for Single-Cell Genomic Data Analytics, started by a MIDAS Challenge Award. These awards aim to bring together data scientists and domain experts to solve real-world problems, leveraging data science services and infrastructure within U-M.
Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Program
With more than $10 million in support from Schmidt Futures, MIDAS will hire 10 postdoctoral fellows annually for up to six years and provide intensive training and research experience as they ready themselves for independent research in academia and other sectors. This new program will complement the Michigan Data Science Fellows Program, elevating University of Michigan’s standing among postdoctoral training programs for data science and AI.
Center for Data-Driven Drug Development and Treatment Assessment (DATA)
With funding from the National Science Foundation’s Industry-University Cooperative Research Centers (NSF IUCRC) program, MIDAS will establish the Center for Data-Driven Drug Development and Treatment Assessment (DATA). This center will brings together domain experts to develop reproducible methodologies that will make a broad impact on drug discovery.
Data Science Training Workshops for U-M Researchers
MIDAS offered intensive workshops, multi-day bootcamps, and seminars to provide U-M researchers with the requisite training to successfully apply data science techniques to their research questions and strategies for integrating data science into their grant applications. This past year, MIDAS focused programming on the disciplines of biomedical data science, environmental data science, and Natural Language Processing.
Annual Data Science and AI Summit, 2022
Bringing together the U-M data science and AI research community and their external collaborators, the annual Summit aims to build research vision and collaboration. This two-day showcase illustrates the breadth and depth of U-M data science and AI research, from theory and methodology development to the transformative use of data and AI to address scientific and societal challenges in all domains.
NSF Civic Innovation Challenge grant supports collaborative project between the Little Traverse Bay Bands of Odawa Indians and U-M
Building upon a collaborative data for social good project started in summer of 2021, LTBB and MIDAS have secured a National Science Foundation (NSF) Civic Innovation Challenge stage 1 grant to plan a centralized and comprehensive database that helps to accurately capture the condition of the Tribal Nation and its citizens.
Inaugural Rocket Companies Michigan Data Science Fellow
Bernardo Modenesi joins MIDAS as the inaugural Rocket Companies Michigan Data Science Fellow. Generously supported by Rocket Companies, Bernardo's research will focus on labor market dynamics with considerations of fairness and ethical practices in mind.
Danai Koutra earns ICDM 10-Year Highest Impact Paper Award
Associate Professor and Associate Director of MIDAS Danai Koutra and her co-authors have been recognized with the ICDM2022 10-Year Highest Impact Paper Award, which recognizes the most influential paper among those published at ICDM 2013. Her paper examines the use of bipartite graph alignment and paved the way for continued research in graph matching.
Reproducibility Challenge, Round 2
MIDAS promotes reproducible data science together with researchers in our community through raising awareness, celebrating best practices, enabling the scholarly investigation of reproducible research, and developing tools that can be widely adopted.

MIDAS By The Numbers

Affiliated Faculty
External funding secured by research teams who received pilot funding from MIDAS
MIDAS funded research projects
Working Partnerships