Models, Inference & Algorithms (MIA)

The Models, Inference & Algorithms (MIA) Initiative at the Broad Institute supports learning and collaboration across the interface of biology and medicine with mathematics, statistics, machine learning, and computer science. Our weekly meetings are open and pedagogical, emphasizing lucid exposition of computational ideas over rapid-fire communication of results. Learn more about MIA and its history.


Upcoming Talks

Upcoming MIA Talks

Spring 2026 talk titles, speakers, and abstracts will continue to be updated below. 

Thank you for joining us for our MIA 10-Year Anniversary Celebration this fall! The panel is now available for viewing.

Watch - MIA Over the Last 10 Years.


Quick Links


Meeting Details

Hosted by the Eric and Wendy Schmidt Center, MIA meetings feature a 9:00 am primer with breakfast, 10:00 am seminar, and 10:50 am discussion. They are located at the Broad Institute in Acadia (75 Ames St., M1) unless noted otherwise, and virtually.

If you do not have a Broad badge, please arrive 10 minutes early to 75 Ames St. with an ID to check in with security. We will escort folks up at 8:55 am and 9:55 am -- email mia-team@broadinstitute.org if you arrive outside of those times.

Please email mia-team@broadinstitute.org to join our mailing list for event updates and Zoom links.


Current Steering Committee and Organizers

Current co-chairs: Orr Ashenberg (since Sept '23), Lauren Golden (since April '25).

MIA's efforts are driven by the Steering Committee: Ghamdan Al-Eryani, Orr AshenbergTavor Baharav, Jessika BaralSalil Bhate (co-chair, Jan '23 - May '24)Sebastiano Cultrera di MontesanoPinar Demetci (co-chair, Jan '24 - June '25), Laura DrepanosLauren GoldenSumaiya Iqbal, Tanvi Jain, Ruitong LiDR Mani, Joshua PickardGio PanagiotaropoulouMarie-Madlen PustAkshaya Thoutam, Yuna Zhang, Sam Zimmerman.

Admin: Suus Bergenhenegouwen, Jorge FortinNadya Karpova.

Founders: Alex BloemendalJon Bloom (fall 2015).

MIA Talks Search

Spring 2026
Date Speaker Title
Feb 4
Characterizing homology-induced data leakage and memorization in genome-trained sequence models Spring 2026
Feb 4
More robust data, models, and benchmarks to solve the genome regulation code Spring 2026
Feb 11
  • Harvard T.H. Chan School of Public Health

FlowMap: Geometry-Preserving Embedding of RNA Velocity Spring 2026
Feb 11
  • Harvard T. H. Chan School of Public Health

Modern Nonlinear Embedding Methods Unpacked: Empowering Biological Discoveries with Statistical Insights Spring 2026
Mar 4
Physics-constrained models for microbial community inference Spring 2026
Mar 4
Predicting and programming microbial communities across scales Spring 2026
Mar 18
Understanding Spatial Transcriptomics and Evaluating Probe Accuracy in 10x Genomics Xenium Technology Spring 2026
Mar 18
Comparative Spatial Transcriptomics Analysis Spring 2026
Apr 1
STATE: Predicting cellular responses to perturbation across diverse contexts Spring 2026
Apr 1
Engineering cell state using artificial intelligence Spring 2026
Apr 15
AI agents in biomedical research Spring 2026
Apr 15
Evaluating the autonomous and copilot limitations of AI agents for biological discovery Spring 2026
Apr 22
Mapping phenotypes to spatial transcriptomics reveals disease-associated microenvironments with PhAST Spring 2026
Apr 22
Resolving Tissue Maps: Statistical and Deep Learning Methods for Integrative Spatial Omics Across Samples, Sections, and Modalities Spring 2026
May 6
Primer Spring 2026
May 6
A global microbiome axis underlying susceptibility to immune-mediated diseases Spring 2026
May 13
Learning, Predicting, and Interpreting Omics Data with Biologically Informed Models Spring 2026
May 20
Parameter representations outperform single-cell foundation models on downstream tasks Spring 2026
May 27
  • Speakers to be announced

Flash talks Spring 2026
Jun 3
Talk title coming soon Spring 2026