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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 meeting features a primer, breakfast, seminar, and discussion; these are open and pedagogical, emphasizing lucid exposition of computational ideas over rapid-fire communication of results. Other MIA functions include hosting workshops, developing educational resources, advising leadership, and supporting the computational community.

 

Current co-chairs: Aleksandrina Goeva (since Jan 2021) & Thouis Jones (since Jan 2022)

MIA's efforts are driven by the Steering Committee: Alex Bloemendal (co-chair, Fall 2015 - Jan 2022)Anika GuptaArnav MehtaBrian ClearyElizabeth Wood, Emma Stickgold, Juan Caicedo, Lois Doolittle, Martin JankowiakMarzieh HaghighiMehrtash Babadi, Mollie Morg, Mor NitzanRay Jones, and Sam Friedman.

Jon Bloom and Alex Bloemendal founded MIA in Fall 2015. Jon Bloom served as a co-chair through July 2019. Past Steering Committe members: Allen GoodmanDebora MarksDavid BenjaminDylan KotliarGopal Sarma (co-chair, Jul 2019 - Jan 2021), James McFarlandJon Bloom, Hilary FinucaneSam RiesenfeldYakir ReshefAviad Tsherniak and Max Shen.


MIA Overview: Watch this introduction to the past, present, and future of MIA, and how you can help drive the fusion of machine learning and biomedicine. Check out the Kendall Square Codebreakers in the Harvard Crimson.


MIA Playlist: Watch and share our growing library of MIA videos.


Talking Machines: Listen to interviews with Eric LanderAviv Regev, and Nick Patterson.

Spring 2022 Schedule: 9am Primer, 10am Meeting, 10:50am Discussion unless noted otherwise, via Zoom. Please refer to our MIAcast (weekly email announcement) for Zoom meeting information. Email lrosinsk@broadinstitute.org with questions and mia-team@broadinstitute.org to be added to our mailing list.

Date Speaker Title
Jan 19
Primer: Comparing gene expression data across species using evolutionary methods (note: 10am start)
Jan 19
  • Depts. of Organismic and Evolutionary Biology, Molecular and Cellular Biology, Harvard University; Howard Hughes Medical Institute
Developing a systems approach to understanding adaptive evolutionary change using Hawaiian Drosophila as a model clade (note: 11am start)
Jan 26
NO MEETING THIS WEEK
Feb 2
Primer: Canonical correlation analysis and the structure of psychedelic experience; Towards a neurophenomenological cartography of the cortex
Feb 2
Trips and neurotransmitters; Discovering principled patterns across 6850 hallucinogenic experiences
Feb 9
Primer: A deep learning approach to structural variant discovery
Feb 9
Cue: A framework for cross-platform structural variant calling and genotyping with deep learning
Feb 16
  • Computational Biology and Data Science group, Vesalius Therapeutics
Primer: Clarifying confusion in scRNA-seq analysis
Feb 16
  • Dept. of Human Genetics, and the Research Computing Center, University of Chicago
Learning the "parts" of cells using topic models
Feb 23
NO MEETING THIS WEEK
Mar 2
  • Apple; Center for Research in Economics and Statistics, Institut Polytechnique de Paris
Primer: From matchings to optimal transport, use cases and algorithms
Mar 2
  • Dept. of Computational Health, Helmholtz Munich; Dept. of Mathematics, Technical University of Munich
Moscot: A scalable toolbox for optimal transport problems in single cell genomics
Mar 9
Primer: Capturing structure in high-dimensional data using K nearest neighbor graphs
Mar 9
  • Raychaudhuri Lab, Bioinformatics and Integrative Genomics Program, Harvard Medical School
  • Raychaudhuri Lab, Harvard Medical School; Brigham and Women’s Hospital
Quantifying axes of inter-sample variability among transcriptional neighborhoods in single-cell datasets
Mar 16
NO MEETING THIS WEEK
Mar 23
NO MEETING THIS WEEK
Mar 30
No Primer
Mar 30
  • Eric and Wendy Schmit Center Postdoctoral Fellow, Caicedo and Uhler labs, Broad Institute
Towards semantic representations of tissue organization from high-parameter imaging data
Apr 6
No Primer
Apr 6
  • Deep Learning Group, Microsoft Research
Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
Apr 13
The impact of climate, social setting, and susceptibility on dengue dynamics: a case study using compartmental models, empirical dynamic modeling, and meta-analysis; Part I
Apr 13
  • Dept. of Biology, Stanford University; Center for Computational, Evolutionary and Human Genomics
  • Dept. of Biology, Stanford University; University of British Columbia
The impact of climate, social setting, and susceptibility on dengue dynamics: a case study using compartmental models, empirical dynamic modeling, and meta-analysis; Part II
Apr 20
NO MEETING THIS WEEK
Apr 27
Primer: TBD
Apr 27
  • Dept. of Molecular Cell Biology, Weizmann Institute of Science
Design principles of hormone circuits
May 4
NO MEETING THIS WEEK
May 11
Primer: Scaling microbial dynamics with Bayesian nonparametrics
May 11
  • Division of Computational Pathology, Brigham and Women’s Hospital, Harvard Medical School; Massachusetts Institute of Technology
Intrinsic instability of the dysbiotic microbiome revealed through dynamical systems inference at ecosystem-scale
May 18
NO MEETING THIS WEEK
May 25
No Primer
May 25
Deep learning based morphological profiling for rare diseases genomic medicine