Overview
The Michigan Institute for Data and AI in Society (MIDAS) invites U-M researchers to kick off the 2026-27 academic year at our annual Welcome-Back Social and Faculty Research Pitch, bringing together researchers, students and collaborators from across the university to connect, share ideas and explore new opportunities in data science and AI.
The event will feature short (3 min) faculty research pitches, with a special focus on researchers who are new to U-M or have joined the MIDAS community within the past year. This is an opportunity to introduce your work, connect with a diverse network of researchers and spark new collaborations across disciplines.
With more than 750 MIDAS faculty affiliates representing schools, colleges and research areas across U-M, this event helps build connections that can lead to new partnerships, funding opportunities and interdisciplinary research. Previous research pitches have helped inspire collaborations supported through initiatives such as MIDAS’s Propelling Original Data Science (PODS) grants.
Attendees will have the opportunity to connect with MIDAS faculty affiliates, researchers and students, learn about upcoming MIDAS programs and initiatives, and discover opportunities for collaboration, funding and training.
All U-M researchers are welcome to attend.
To give a research pitch (3 minutes, 3 slides) on any aspect of your research, for example, your research vision, or a new direction / project idea to seek faculty collaborators or students, presenters must be MIDAS-affiliated faculty members.
Register for the event to submit a pitch.
Researchers interested in joining MIDAS can complete the affiliate application form.
Schedule
The annual Welcome back Social and Faculty Research Pitch will be held on Monday, September 14, from 2:00-4:00 PM in Palmer Commons, Great Lakes Room, 100 Washtenaw Ave, Ann Arbor, MI.
Anyone who plans to attend the event (as an audience member or a speaker) should please register.
2026 Speakers
Olanrewajuj Aluko
Professor of Mechanical Engineering, The University of Michigan-Flint
Molecular dynamics simulations and machine learning for nanoscience and technology.
Dylan Cable
Assistant Professor of Biostatistics, School of Public Health
Statistical and machine learning methods for spatial transcriptomics
Saptarshi Chakraborty
Assistant Professor of Statistics, College of Literature, Science, and the Arts
Breaking the Curse of Dimensionality in Diffusion Models
Yun Chen
Associate Research Scientist, Mechanical Engineering, College of Engineering
From Sensors to Observing Systems: AI-Driven Environmental Monitoring Under Real-World Constraints
Ssu-Ying Chen
Data Science Analyst
Anesthesiology, Michigan Medical School
Automated Clinical Indication Extraction and HPO Mapping Using LLMs
Rose Cory
Professor of Earth and Environmental Sciences, College of Literature, Science, and the Arts
How will thawing permafrost in the Arctic alter Earth’s carbon cycle?
Huteng Dai
Assistant Professor of Linguistics, College of Literature, Science, and the Arts
Language Modeling with Cognitively Plausible Memory
Yulong Dong
Assistant Professor of Electrical Engineering and Computer Science, College of Engineering and Assistant Professor of Mathematics, College of Literature, Science, and the Arts
Mathematical Analysis of Noisy Quantum Machine Learning
Lauren Gillespie
Assistant Professor, School for Environment and Sustainability
Foundation models for ecosystem analysis
Michael Karsy
Clinical Assistant Professor of Neurosurgery, Michigan Medical School
Methods and Strategies to Improve Surgical Vision in Neurosurgery
Suzanne Perkins
Research Assistant Professor, Institute for Social Research
Developing an AI Cross-Sector Narrative Injury (CSNI) Paradigm for IPV and Child Maltreatment-Related TBI
Ravi Prakash
Research Assistant Professor of Physical Medicine and Rehabilitation, Michigan Medical School
Genetic Susceptibility to Glenohumeral Osteoarthritis
David Sears
Associate Professor of Music Theory, School of Music, Theatre, and Dance
Music Listening Across the Globe
Yulun Tian
Assistant Professor of Robotics, College of Engineering
Spatial AI for Robot Teams That Remember, Reason, and Scale
Weichao Tu
Associate Professor of Climate & Space Sciences and Engineering, College of Engineering
Physics-Informed Machine Learning for Near-Earth Space Weather Forecasting
Sushil Varma
Assistant Professor of Industrial and Operations Engineering, College of Engineering
Stochastic Matching Networks
Joyce Yan-Ran Wang
Assistant Professor of Biomedical Engineering, College of Engineering and Michigan Medical School
Advancing Healthcare Through AI and Machine Learning Innovations
Feige Wang
Assistant Research Scientist, Astronomy, College of Literature, Science, and the Arts
Astronomy in Big Data Era
Nari Yoo
Assistant Professor, School of Social Work
Generative AI for Immigrants, Refugees, and Service Providers
Ling-Yu Liu
Research Investigator, School of Dentistry
Toward Autonomous Dental Sensorimotor Phenotyping: Integrating Jaw-Opening, Breathing, and Grimace Responses with Multimodal AI
FAQ
Anyone interested in learning more about, becoming involved in, or meeting new people in the U-M data science and AI research ecosystem, but especially MIDAS-affiliate faculty members, new U-M faculty members and those new to MIDAS, students or postdocs seeking faculty mentors and projects.
Presenters will give a three-minute research pitch, with up to three slides, followed by one question.
Audience members will vote for the “Best Research Pitch” after the presentations.
Attendees will have ample time to network with fellow U-M researchers who share common research interests.
You can present anything you’d like people to know about your research. It could be an overview of your research, or a specific project that needs collaboration or students, or bold ideas that you want feedback about.
Consider the following:
- How do you tell a compelling and clear story?
- What do you want the audience to learn from your pitch?
- How does your story help you achieve your goal of giving a pitch?
Audience members will select the “Best Research Pitch” awards.
Following the event, we will publish all research pitch videos to the MIDAS YouTube channel and website.
Contact Us
We are excited to showcase your research and to help you make connections in our community and across other institutions.
For questions, please contact Nathan Fox, MIDAS AI Scientist, [email protected].