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, emphasising 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: 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 ThoutamSam 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
Talk title coming soon Spring 2026
Mar 18
Talk title coming soon Spring 2026
Apr 1
Talk title coming soon Spring 2026
Apr 1
Talk title coming soon Spring 2026
Apr 15
Talk title coming soon Spring 2026
Apr 15
Talk title coming soon Spring 2026
Apr 22
Talk title coming soon Spring 2026
May 6
Talk title coming soon Spring 2026
May 6
Talk title coming soon Spring 2026
May 13
Talk title coming soon Spring 2026
Jun 3
Talk title coming soon Spring 2026