Data and AI Intensive Research with Rigor and Reproducibility (DAIR³)
The Data and AI Intensive Research with Rigor and Reproducibility (DAIR3) program includes weeklong
bootcamps in the summer that focus on ethical issues in biomedical data science; data management,
representation, and sharing; rigorous analytical design; the design and reporting of AI models;
generative AI; reproducible workflow; and assessing findings across studies. Additionally, the bootcamp
also includes grant writing sessions and research collaboration discussions.
The program has three components:
Objectives:
At the conclusion of this activity, participants will be able to:
- Design and implement a training program in their home institution that replicates the key elements of this research collaboration training program.
- Carry out better data- and AI-intensive research.
2026 APPLICATIONS CLOSED
Please check back in the fall for next year’s application
Learn cutting-edge data science and Artificial Intelligence (AI) methods for biomedical and healthcare research, ensure the rigor and reproducibility of your projects, and network with fellow attendees from around the country. At the end of the bootcamp, trainees will submit an implementation plan, and in the year after, with the support of a designated mentor, implement new skills in research and teaching.
Open to university faculty and research scientists.
Participation in the training program is free of charge. Scholarships are available.
To learn more about the program, visit the curriculum page.
For more information, visit our FAQ.
Bootcamp Session #1
Monday, May 18 – Saturday, May 23, 2026
University of Michigan – Ann Arbor, MI
Bootcamp Session #2
Monday, June 8 – Saturday, June 13, 2026
University of Texas at San Antonio – San Antonio, TX
For additional questions, please email our DAIR3 program team at: dair3-contact@umich.edu.
Testimonials From Past Bootcamp Attendees
I have been appointed assistant professor of research in the Department of Biological Sciences at the University of Texas at El Paso, where I will focus on data-intensive biomedical research and integrating AI into biological discovery beginning in fall 2025.
The DAIR3 program played a pivotal role in this transition. Through its emphasis on reproducible workflows and AI-driven biomedical data analysis, I was able to strengthen my research and teaching portfolio well beyond my previous role as a Systems Analyst. I am truly grateful for the support and opportunities the DAIR3 experience provided, and I look forward to applying these skills in my new role.
—Khodeza Begum Mitchell, assistant professor of research, Department of Biological Sciences, University of Texas at El Paso
Other testimonials
“Learning valuable topics that helped me navigate a successful thesis defense!”
“Enhancing my knowledge about AI and the ability to work with colleagues from other states with various experiences.”
“One of the most meaningful experiences I had during the DAIR³ summer training bootcamp was designing my own course implementation plan that connected advanced data engineering principles with the ethical and reproducible handling of biomedical data.”
“This experience stood out because it pushed me to think beyond just tools and technologies—it encouraged me to incorporate principles like rigor, reproducibility, and data confidentiality directly into curriculum design. I realized that technical excellence means little without ethical responsibility, especially in biomedical contexts.”
“Collaborate with a diverse group of researchers and technical staff from various fields, engaging in intensive learning sessions and discussions.”
“I appreciated the lightning talks to see what everyone was working on and how rigor and reproducibility works into all of our work.”
Please note that CME credit is only available for the bootcamp.
ACCME Accreditation Designation:
This activity has been planned and implemented in accordance with the accreditation requirements and
policies of the Accreditation Council for Continuing Medical Education (ACCME) through the joint
providership of the University of Michigan Medical School and the Michigan Institute for Data and AI in
Society (MIDAS), Jackson State University, University of Texas at San Antonio, and the College of William
and Mary. The University of Michigan Medical School is accredited by the Accreditation Council for
Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The
University of Michigan Medical School designates this Live Activity for a maximum of 37.25 AMA PRA
Category 1 Credit(s)TM. Physicians should claim only the credit commensurate with the extent of their
participation in the activity.