Priority Application deadline: 11:59 pm EST, Wednesday, April 2, 2025
— click here to Apply —Applications received after April 2 will be reviewed on a rolling basis until all spots are filled.
Academy Overview
The three-day Data- and AI-intensive Research with Rigor and Reproducibility for U-M Biomedical Researchers Summer Academy 2025 is designed for University of Michigan biomedical researchers and faculty.
The rigor of scientific research and the reproducibility of research results are essential for the validity of research findings and the trustworthiness of science. However, research rigor and reproducibility remains a significant challenge across scientific fields, especially for research with complex data types from heterogeneous sources, and long data manipulation pipelines. This is especially critical as data science and artificial intelligence (AI) methods emerge at lightning speed and researchers scramble to seize the opportunities that the new methods bring.
Participants will develop the intellectual framework and technical skills to ensure the rigor and reproducibility of biomedical and healthcare research with cutting-edge data science and artificial intelligence (AI) methods. Specific topics include ethical issues in biomedical data science, data management, representation, and sharing; rigorous analytical design; the design and reporting of AI models; generative AI; and reproducible workflow.
Participants are expected to bring a laptop for programming components of the academy.
Light breakfast options will be available daily. A dedicated lunch reception is planned for Wednesday.
Academy Details
Click each section for more details
By the conclusion of the Academy, participants will develop the intellectual framework and technical skills to ensure the rigor and reproducibility of biomedical and healthcare research with cutting-edge data science and artificial intelligence (AI) methods.
- Internal Participants (University of Michigan researchers and faculty who carry out biomedical, clinical and healthcare research that is data-intensive)
- Cost: $120
This academy workshop is open only for University of Michigan researchers and faculty who carry out biomedical, clinical and healthcare research that is data- and / or AI-intensive.
Summer academies are designed with faculty, staff, and postdocs in mind. Students are also welcome to apply, though priority will be given to faculty, staff, and postdocs.
- More than 14 days before the first day: full refund minus $50 processing fee
- Cancellation between 7 and 14 days of the first day: 50% refund
- Less than 7 days: no refund
- Meet institutional training requirements for human subject research (e.g. CITI Training certificate etc).
- Some experience in study design, data processing and analysis, and reporting.
- Conceptual understanding about the processes of data science projects and methodologies covered in the units, so that they understand critical decisions to support rigor and reproducibility.
It is possible that some trainees will need to acquire prior knowledge in order to participate in the academy, for example, learning the very basics of R or Python. The instructors will provide pre-reading materials and tutorials as needed.
In-person on Central Campus. Specific location to be announced soon.
Parking available nearby includes a parking structure for U-M Blue/Gold permit holders, located at 525 Church St., and metered street parking along Church St. There is also a public garage at 650 S. Forest Ave. View available public parking in Ann Arbor here and real time occupancy counts and public parking structures here.
Instructors
Johann Gagnon-Bartsch
Assistant Professor, Statistics, LSA
H.V. Jagadish
Edgar F Codd Distinguished University Professor and Bernard A Galler Collegiate Professor. EECS, College of Engineering; MIDAS Director
Jing Liu
MIDAS Executive Director
Kerby Shedden
Professor, Statistics, LSA, Biostatistics, School of Public HealthDirector of Consulting for Statistics, Computing, and Analytics Research (CSCAR)
Arvind Rao
Associate Professor, Computational Medicine and Bioinformatics, Michigan Medicine Radiation Oncology, Michigan Medicine Biomedical Engineering, College of Engineering
Academy Schedule
8:30 AM – 4:30 PM each day
*Subject to change
Click each section for more details
Day 1
- Responsible research principles in the context of data and AI
- Ethical considerations for data and AI
- Responsible Conduct of Research in the age of AI
- Rigor as a key considerations in statistical design
Day 2
- Building robust ML models and critically evaluating ML models
- All about data
- Data representation and metadata to make data “AI ready”
- Privacy with data and AI
Day 3
- Packaging research projects for reproducibility
- Meta-analysis as the assessment of the rigor and reproducibility of published results
Questions? Contact Us.
Contact Faculty Training Program Manager, Kelly Psilidis at [email protected]