News

The Michigan Institute for Data Science (MIDAS) announced the awardees of the 2023 round of Propelling Original Data Science (PODS) Grants. Nine teams will receive funding support for a wide range of exciting projects with data science and Artificial Intelligence (AI) as the common thread, including topics such as multimodal learning for disease prediction, using video data to study political discourse, text analysis to detect and reduce bias in graduate admissions, and explainable AI for building trust in AI-aided decisions. The awarded projects are: 

Since 2016, MIDAS has been offering funding to U-M faculty to enable groundbreaking disciplinary and interdisciplinary research through data science and AI, making it possible for research teams to form many new collaborations, formulate groundbreaking ideas, and secure external funding to expand their work. As of 2022, a total of $12M MIDAS funding has jump-started 63 research projects, which expanded into 112 follow-on projects with $114M of external funding. In addition, “year after year, the applicants propose to employ increasingly more sophisticated data science and AI methods to address increasingly more profound research questions,” says Dr. H. V. Jagadish, Director of MIDAS. “This reflects the rapid advancement of data science and AI and their transformation of science and society, and U-M researchers are at the forefront of it.”

The 2023 PODS teams will present their projects at the U-M Annual Data Science and AI Summit to be held November 13-14, 2023. Read more about their projects:

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:

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.

Notes on the Road

Michigan Road Scholars 2023

Written by MIDAS Executive Director Jing Liu. Viewpoints and opinions expressed are her own.

The Michigan Road Scholars tour is a one-week road trip organized by the University of Michigan Vice President for Government Relations Office. 30 scholars, mostly faculty, visit many parts of the state to get to know our communities and people, their passions and challenges, and our natural environment.  Given that I work in a data science and Artificial Intelligence (AI) institute, I wanted to see how data and AI are impacting our state and explore the opportunities they present. I was fortunate enough to be selected among many applicants to participate in the program this year, and was on the road May 1-5.

Working is beautiful

This was a quote from a book that I read as a kid. I don’t even remember the name of the book, but this quote stayed with me for all these years. Being at work, especially doing something you love or are good at, gives so much meaning to our lives: our self worth, fulfillment, and contribution to society.

On the road, I met so many people who demonstrate that working is beautiful:

• Ryan, the manager in the Detroit Diesel engine plant (upper left), whose pride in his plant and in his work was obvious in everything he said.
• The incarcerated individuals in the Vocational Village at Handlon Correctional Facility (upper right), who are taking classes in carpentry, welding, auto repair and more, getting high school diplomas and taking college classes.
• The many passionate women who started their microbusinesses through the help of Build Institute (bottom left).
• In Detroit, we heard about how Lafayette Green (bottom right), a community garden, employs teenagers to both plant trees for Detroit and to help them build work ethics.

What struck me the most is that every one of them is so passionate and knowledgeable about their work.

Resources, labor and the American privilege

The other side of the story is the lack of resources prevalent across the organizations and individuals whom we met, including schools, public universities, and community colleges from Detroit to all the way up north; rural healthcare systems; Native American tribal nations; and a housing shortage spanning the entire state.

By the end of the first day, I had already learned one of the biggest lessons of this trip: I am always proud that I work really hard, but so many people out there work just as hard with far fewer resources.

Up north, we also heard from a few groups of people about the lack of labor. Hotels are hiring workers on temporary visas from other countries to run their day-to-day operations. We looked around in the houses that Habitat for Humanity is building. By American standards, these are pretty basic starter homes with three bedrooms and all the necessary amenities. But here is when I remembered how my family of four lived in one 160-square foot room for years in China when I was a child, and some of my friends lived in even smaller homes. One of my fellow Road Scholars said that, when he was a child in India, he and his three siblings slept on the floor of his grandma’s room. As our communities face so many challenges because of the lack of resources, how do we keep our effort in the context that the US has 4.25% of the world population but 31% of the wealth?

We – the US – certainly don’t lack resources. How can we ensure that these resources reach the people who really need them? How can data scientists help to both raise awareness of the resource inequalities and their impact on the entire society, and support data-informed policies?

Will AI take over?

While we marvel at so many people’s passion about their work, we are also concerned about how robots, GPTs and other forms of AI are reshaping the nature of work.

• At the Detroit Diesel engine plant, what struck us was the extent of automation (pic 1). Few workers were around, the vast 3 million square feet of the factory floor were mostly run by automated processes, machines and robots.
• At the LaFarge cement factory in Alpena (pic 2) – the largest cement plant in the world by some records – with an annual output of 2.4M tons of cement and with the plant running 24/7, there are a total of only 280 employees.
• At the dinner with the Old Town Playhouse and their senior performance group Aged to Perfection, the seniors talked with me about whether they’d trust AI when it replaces experienced doctors to make diagnosis and treatment plans.
• At the Enbridge oil pipeline (pic 3), workers talked about using AI to predict water traffic safety breeches.

What will the workplace look like in two, five, or ten years? When the incarcerated individuals in the vocational village receive certificates in carpentry or auto repair, when the next generation of factory floor workers are ready to seek jobs, what jobs will await them? How are we preparing for the age when humans and AI co-exist?

Academia, government, community, industry and the need to collaborate

We are embracing a fast-changing world. New technologies such as AI are rapidly changing our definition of work, human relationships, and even what is human. Data and the capability of using data to guide policy are enriching the already rich communities and leaving others behind. Climate change is happening in front of our eyes. How we preserve and seek livelihood, fulfillment and dignity in this new world is something too big for anyone to tackle alone. This is the time when we ALL need to work together.

Celebrating people, community, and our natural habitats

Thunder Bay Diving Center. Credit: NOAA

• At Archangel Ancient Tree Archive in Copemish, we saw how David Milarch’s family uses modern biotechnology to clone ancient trees that could help reverse climate change (upper left).
• At the Little Traverse Bay Bands of Odawa Indians, we learned about how they respect the animals that they hunt (upper right).
• At 9 Bean Rows Farmstead, we learned how the farmers supported each other during the pandemic (lower left).
• At Thunder Bay, we heard about how local students learn technical skills and help preserve the Great Lakes through working with the National Oceanic and Atmospheric Administration (lower right).
• (bottom) In Traverse City, we had dinner with community theater members and watched plays performed by Aged to Perfection – seniors from 55 to 93, who performed with energy, humor, wisdom, and charm. One woman in her 80s told me about how hard it was for her in her 20s to pursue a job that was neither a teacher nor a nurse. I asked her, if she could go back in time, what she would say to her 25-year-old self. Her answer: “Don’t let anyone tell you you can’t.”

They are the reasons why we work hard in the first place.

During the last holiday season, millions of people worldwide experienced what it was like to let ChatGPT write an essay, debug code, or dispense sage advice. They also witnessed firsthand just how smoothly ChatGPT could make up information that it didn’t know.

Artificial Intelligence (AI) is rapidly claiming its place in everything we do: it drives cars and fighter planes; it detects cancer in radiological images and black holes in telescope images; it helps us choose which songs to listen to; it helps government offices decide who gets welfare; it even designs and runs experiments, even faster than scientists are able to.

As a campus-wide organization to support data science and AI research, one focus area of the Michigan Institute for Data Science (MIDAS) is to enable the use of data science and AI to accelerate scientific discovery. During the Winter 2023 semester, MIDAS faculty affiliates, postdocs, and campus collaborators organized colloquia on “Automated Research Workflows”, “Data Justice, AI and Design” (jointly with Taubman College and the Center for Ethics, Society and Computing), and “AI in Science and Engineering.” The fourth and final one of this semester, “Implementing AI in Health,” will take place on April 17 as a joint event of MIDAS and the Department of Learning Health Sciences. These events brought together experts from around the country and U-M faculty to stimulate research ideas and collaboration.

Yet, this rapid advancement of AI is also challenging some of our fundamental beliefs. What is unique about being human, when machines can write novels, compose music, and beat the chess world champion? To address these complicated questions, MIDAS, LSA and the AI Lab organized a panel discussion in February on how AI tools challenge traditional thinking about classroom learning. On April 19, the second installment, hosted jointly with the School of Music, Theatre and Dance, will focus on generative AI, music composition, the meaning of creativity, and the challenges AI poses to intellectual property.

The fascination about AI also coexists with uneasiness. The increasingly complex AI tools, sometimes in combination with flawed data, can give rise to harm in many ways, including the magnification of disinformation or surveillance capitalism, that will perpetuate or amplify existing biases and injustice. The concerns about the ethical and responsible use of AI are also not limited to human research. Ecologists need to consider whether their datasets are inclusive of endangered species. Jet engine designers need to know that their AI-engineered solutions are safe for humans. How can academic researchers address these concerns as AI developers and users? Another focus area of MIDAS is exactly to promote responsible data science and AI.

The 2023 Future Leaders Summit recently took place, with the theme of “Responsible data science and AI”. This MIDAS annual event brings together outstanding Ph.D students and postdocs from major research universities, midwest universities, and minority-serving universities, with the majority of the attendees being women and under-represented minorities. Trainees listened to vision talks from mentors, gave research presentations, attended career mentoring sessions, and networked with peers. The focus on responsible data science and AI helps to prepare these trainees, who will be the next generation of academic leaders in data science and AI, to maximize the positive impact of data and AI, while preserving the ideals and values of our society.

The Summit included a mini-symposium with the following speakers:

• H. V. Jagadish, University of Michigan, “Equity in data science.”
• Ellie Sakhaee, Microsoft, “Building a culture of Responsible AI (and what it means for researchers)”
• Tanya Berger-Wolf, the Ohio State University, “Human-machine partnership for conservation: AI and humans combatting extinction together”
• Andrew J. Connolly, University of Washington, “From interstellar rocks to dark energy: building data science across research communities.”

On May 16, 2023, MIDAS will offer From Theory to Practice: Building Ethical and Trustworthy AI, a forum jointly organized with Rocket Companies that will feature speakers from academia, industry and government on the ethical use of AI and its regulation. Readers can still submit abstracts for lightning talks.

“Humans constantly grapple with how new technological advances fit into our moral and ethical framework. But the massive amount of data in the world today and how quickly AI is getting more powerful makes this the critical moment for ethical data science and AI.” Says Dr. H. V. Jagadish, MIDAS Director. “We look forward to working with all researchers to tackle this challenge together.”

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.