MIA Talks Search

Spring 2024
Date Speaker Title
May 29
  • Marinka Zitnik

    Harvard University and Stanford University 

TBD Spring 2024
May 8
  • Matthew McPartlon

    Chai Discovery, AI Research, VantAI

Protein Design with Deep Learning: Progress, Challenges, and Next Steps Spring 2024
May 8
  • Joshua Meier

    Chai Discovery

Unlocking Generative AI for Drug Discovery with Zero-shot Models Spring 2024
May 1
  • Sergey Ovchinnikov

    MIT

Protein language models learn evolutionary statistics of interacting sequence motifs Spring 2024
May 1
  • Simon Kozlov

    MIT

Combining protein language and structure models to redesign E. coli proteome with a reduced amino acid alphabet Spring 2024
Apr 10
  • Aparna Nathan

    Lecturer on Biomedical Informatics, Harvard Medical School

Single-cell models for state-dependent eQTL analysis Spring 2024
Apr 10
    • Raychaudhuri Lab, Division of Genetics/Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital.
    • Department of Medicine, Harvard Medical School.
Scalable single-cell models for robust cell-state-dependent eQTL mapping Spring 2024
Apr 3
  • Postdoctoral fellow Eric and Wendy Schmidt Center Broad Institute

Statistical and algorithmic challenges in reference-free analysis Spring 2024
Apr 3
SPLASH unifies genomic analysis and discovery through a paradigm shift to statistics-first Spring 2024
Mar 20
Testing data-driven hypotheses post-clustering
[Video]
Spring 2024
Mar 20
  • Assistant Professor of Statistics

    University of British Columbia

Data thinning to avoid double dipping
[Video]
Spring 2024
Mar 13
  • Žiga Avsec

    Google DeepMind

Accurate proteome-wide missense variant effect prediction with Alpha Missense Spring 2024
Mar 13
  • Jun Cheng

    Google DeepMind

Alpha Missense Spring 2024
Mar 6
  • Sandeep Kambhampati

  • Philipp Schneider

  • Kai Cao

  • Bojan Karlas

Postdoc flash talks Spring 2024
Feb 14
  • Pascal Notin

Hybrid protein language models for fitness prediction and design
[Video]
Spring 2024
Feb 14
Unsupervised viral antibody escape prediction for future-proof vaccines
[Video]
Spring 2024
Fall 2023
Date Speaker Title
Dec 6
  • Department of Developmental Biology and Genetics, Washington University in St. Louis

Dissecting cell identity via network inference and in silico gene perturbation
[Video]
Fall 2023
Dec 6
  • Kenji Kamimoto

    Samantha Morris Lab, Washington University in St.Louis

Dissecting cell identity via network inference and in silico gene perturbation
[Video]
Fall 2023
Nov 29 Causal representation learning of genetic perturbations: identifiability and combinatorial extrapolation
[Video]
Fall 2023
Nov 29
  • Regev Lab, Genentech & Pritchard Lab, Stanford

Large-Scale Differentiable Causal Discovery of Factor Graphs
[Video]
Fall 2023
Fall 2023
Date Speaker Title
Nov 15
  • David Relman lab and Dmitri Petrov lab, Stanford University

Tracking strains in the human gut microbiome
[Video]
Fall 2023
Nov 15
  • David Relman lab and Dmitri Petrov lab, Stanford University

Dynamics of colonization and transmission in the human gut microbiome
[Video]
Fall 2023
Nov 1
An introduction to diffusion models for protein design
[Video]
Fall 2023
Date Speaker Title
Nov 1
diffusion models
Fall 2023
Date Speaker Title
Nov 1
Bridging Biophysics and AI to Optimize Protein Design
[Video]
Fall 2023
Oct 25
  • Microsoft Research New England

Towards Meaningful Pretrained Models for Biology
[Video]
Fall 2023
Oct 25
  • Stanley Hua

    University of Toronto

Meaningful choice/curation of pre-training data in alignment with a downstream task
[Video]
Fall 2023
Oct 25
  • School of Engineering and Applied Sciences, Harvard University

Disentangling Meaningful Signal from Experimental Noise within Deep Learning Models
[Video]
Fall 2023
Oct 18
  • McGill University, Electrical and Computer Engineering, Montréal, Canada

Theoretical background regarding GANs and Causal GAN
[Video]
Fall 2023
Oct 18
  • Amin Emad, Prof

    McGill University and Mila (Quebec AI Institute)

GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks
[Video]
Fall 2023
Oct 11
Lighting talks Fall 2023
Sep 20
  • Xinyi Zhang

    MIT EECS; Eric and Wendy Schmidt Center, Broad Institute

Graph-based autoencoder integrates spatial transcriptomics with chromatin images and identifies joint biomarkers for Alzheimer’s disease
[Video]
Fall 2023
Sep 20
Seurat v5, cross-modality mapping and large-scale clustering of single-cell data
[Video]
Fall 2023
Spring 2023
Date Speaker Title
May 10
A Fourier Tour of Protein Function Prediction
[Video]
Spring 2023
May 10
Leveraging the Sparsity of Epistatic Interactions to Understand and Improve Models of Fitness Functions
[Video]
Spring 2023
Apr 26
  • Ben Deverman

    Broad Institute

ML-compatible experimental approaches to accelerate AAV engineering Spring 2023
Apr 26
  • Fatma Elzahraa Eid

    Broad Institute

Multi-trait protein engineering - a synergistic ML-wet lab approach to AAV engineering Spring 2023
Date Speaker Title
Apr 19
  • James Zou

Generative AI for biomedicine
Spring 2023
Date Speaker Title
Apr 19 Generative AI for biomedicine
[Video]
Spring 2023
Apr 19 How to evaluate medical AI
[Video]
Spring 2023
Spring 2023
Date Speaker Title
Apr 12
Current techniques for case-control comparisons in high-throughput transcriptomics and the need for contrastive methods
[Video]
Spring 2023
Apr 12
  • University of North Carolina at Chapel Hill

Contrastive latent variable models to expose changes in case-control sequencing experiments
[Video]
Spring 2023
Apr 5
Intro to machine learning for molecules, small and large Spring 2023
Mar 22
  • Massachusetts General Hospital, Harvard Medical School
    Associate Member
    Broad Institute of MIT and Harvard
     

Image2Omics: Generating Omics Data from Images
[Video]
Spring 2023
Mar 22
  • Charles Comiter

    Massachusetts Institute of Technology
    Massachusetts General Hospital, Harvard Medical School
    Broad Institute of MIT and Harvard
     

Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF)
[Video]
Spring 2023
Mar 8
  • NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark

Variational autoencoders for analysis and integration of multi-omics and multi-modal data
[Video]
Spring 2023
Mar 8
  • NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark

Deep dive into multi-omics variational autoencoding
[Video]
Spring 2023
Mar 1
  • Haoran Zhang

    MIT

Primer: Group Fairness in Chest X-ray Diagnosis: Helpful or Harmful?
[Video]
Spring 2023
Date Speaker Title
Mar 1
Hiding in plain sight – What does AI’s ability to detect patterns not visible to radiologists mean?
Spring 2023
Date Speaker Title
Mar 1
Hiding in plain sight – What does AI’s ability to detect patterns not visible to radiologists mean?
[Video]
Spring 2023
Feb 15
  • Bruno Correia

    Laboratory of Protein Design & Immunoengineering (LPDI), EPFL

Computational protein design
[Video]
Spring 2023
Feb 15
  • Casper Goverde

    Laboratory of Protein Design & Immunoengineering (LPDI), EPFL

De novo design of proteins
[Video]
Spring 2023
Feb 8
Primer: Charting the Landscape of 3D Genome Organization with Graph Representation Learning
[Video]
Spring 2023
Feb 8
  • Gene Regulation Observatory, Broad Institute; Society of Fellows, Harvard University
     

High-Throughput In Silico Genetic Screen for Discovering Novel 3D Genome Organization Regulation
[Video]
Spring 2023
Feb 1
  • Stanford University School of Medicine

Learning to read and write protein evolution
[Video]
Spring 2023
Fall 2022
Date Speaker Title
Dec 7
  • Principal Researcher at Microsoft

  • Senior Researcher in Machine Intelligence at Microsoft Research

Primer: An Introduction to Causal Discovery and Inference Fall 2022
Dec 7
  • Senior Researcher in Machine Intelligence at Microsoft Research

  • Principal Researcher at Microsoft

Deep End-to-end Causal Inference Fall 2022
Nov 23 NO MEETING WEEK Fall 2022
Nov 16
  • Department of Cellular and Tissue Genomics - Oncology, Genentech

Primer: Analytical challenges and opportunities for studying cell state transitions at the single cell level
[Video]
Fall 2022
Nov 16
Neural Optimal Transport for Inferring Single-Cell Responses to Perturbations
[Video]
Fall 2022
Fall 2022
Date Speaker Title
Nov 2 NO MEETING Fall 2022
Oct 26 No Primer Fall 2022
Oct 26
Deep learning based morphological profiling for rare disease genomic medicine Fall 2022
Oct 19
  • Camargo Lab, Boston Children's Hospital

Primer: Lineage tracing for tissue development and cell differentiation Fall 2022
Oct 19
  • Damon Runyon Computational Biology Fellow, Harvard Medical School

Learning cell differentiation dynamics from lineage tracing datasets
[Video]
Fall 2022
Oct 12
Primer: The envelope of sequence bioinformatics in 2022
[Video]
Fall 2022
Oct 12
  • Department of Molecular Genetics; Donnelly Centre for Cellular and Biomolecular Research; University of Toronto

The limits of Virus Discovery, and how to overcome them
[Video]
Fall 2022
Oct 5
  • ML/NLP for healthcare, Postdoc at Brigham and Women's Hospital / Harvard Medical School

Primer: Promise and Challenges of Language Models in the Clinical Domain
[Video]
Fall 2022
Oct 5
Unlocking the Power of Electronic Health Record data using Deep Learning based Natural Language Processing
[Video]
Fall 2022
Sep 28
  • Postdoctoral Fellow in the Weissman Lab of MIT and Whitehead Institute

Towards predictive spatiotemporal modeling of single cells Fall 2022
Sep 28
Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq
[Video]
Fall 2022
Sep 21
Primer: Gene expression prediction from DNA sequences
[Video]
Fall 2022
Sep 21
  • Assistant Professor, School of Biomedical Engineering UBC

Using deep learning regulatory models and random DNA for evolutionary inference
[Video]
Fall 2022
Sep 14
Primer: An Introduction to Bayesian Variable Selection
[Video]
Fall 2022
Sep 14
Applications of Bayesian Variable Selection to Bioinformatics
[Video]
Fall 2022
Spring 2022
Date Speaker Title
May 25 No Primer Spring 2022
May 25
Deep learning based morphological profiling for rare diseases genomic medicine Spring 2022
May 18 NO MEETING THIS WEEK Spring 2022
May 11
Primer: Scaling microbial dynamics with Bayesian nonparametrics Spring 2022
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 Spring 2022
Spring 2022
Date Speaker Title
May 4 NO MEETING THIS WEEK Spring 2022
Apr 27 Primer: TBD Spring 2022
Apr 27
  • Dept. of Molecular Cell Biology, Weizmann Institute of Science

Design principles of hormone circuits Spring 2022
Apr 20 NO MEETING THIS WEEK Spring 2022
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
[Video]
Spring 2022
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
[Video]
Spring 2022
Apr 6 No Primer Spring 2022
Apr 6
  • Deep Learning Group, Microsoft Research

Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
[Video]
Spring 2022
Mar 30 No Primer Spring 2022
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
[Video]
Spring 2022
Mar 23 NO MEETING THIS WEEK Spring 2022
Mar 16 NO MEETING THIS WEEK Spring 2022
Mar 9
Primer: Capturing structure in high-dimensional data using K nearest neighbor graphs
[Video]
Spring 2022
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
[Video]
Spring 2022
Mar 2
  • Apple; Center for Research in Economics and Statistics, Institut Polytechnique de Paris

Primer: From matchings to optimal transport, use cases and algorithms
[Video]
Spring 2022
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
[Video]
Spring 2022
Feb 23 NO MEETING THIS WEEK Spring 2022
Feb 16
  • Computational Biology and Data Science group, Vesalius Therapeutics

Primer: Clarifying confusion in scRNA-seq analysis
[Video]
Spring 2022
Feb 16
  • Dept. of Human Genetics, and the Research Computing Center, University of Chicago

Learning the "parts" of cells using topic models
[Video]
Spring 2022
Feb 9
Primer: A deep learning approach to structural variant discovery
[Video]
Spring 2022
Spring 2022
Date Speaker Title
Feb 9
Cue: A framework for cross-platform structural variant calling and genotyping with deep learning
[Video]
Spring 2022
Feb 2
Primer: Canonical correlation analysis and the structure of psychedelic experience; Towards a neurophenomenological cartography of the cortex Spring 2022
Feb 2
Trips and neurotransmitters; Discovering principled patterns across 6850 hallucinogenic experiences Spring 2022
Jan 26 NO MEETING THIS WEEK Spring 2022
Jan 19
Primer: Comparing gene expression data across species using evolutionary methods (note: 10am start)
[Video]
Spring 2022
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) Spring 2022
Fall 2021
Date Speaker Title
Dec 1
Polygenic priority score for GWAS gene prioritization
[Video]
Fall 2021
Dec 1
  • Broderick Group, Massachusetts Institute of Technology

A new approach for high-dimensional hierarchical modeling
[Video]
Fall 2021
Nov 24 NO MEETING THIS WEEK Fall 2021
Nov 17 NO MEETING THIS WEEK Fall 2021
Nov 10
  • Van Allen Lab, Dana-Farber Cancer Institute; Broad Institute

Primer: Genomic tools for interpreting patterns of somatic driver and passenger mutations in cancer
[Video]
Fall 2021
Nov 10
Biologically informed deep neural network for prostate cancer discovery
[Video]
Fall 2021
Nov 3 NO MEETING THIS WEEK Fall 2021
Oct 27
  • Depts. of Biochemistry & Biophysics, Urology, University of California San Francisco

Primer: Capturing regulatory information encoded in RNA secondary structure
[Video]
Fall 2021
Oct 27
Computational tools for deciphering the RNA structural code
[Video]
Fall 2021
Oct 20
Lightning talks (9am start, no primer)
[Video]
Fall 2021
Oct 13
  • Seung Lab, Princeton Neuroscience Institute, Princeton University

Scalable analysis of electron microscopy connectomics data: Revealing neural circuit properties using contrastive deep learning
[Video]
Fall 2021
Oct 13
No such thing as unlabeled: Self-supervised learning on medical data
[Video]
Fall 2021
Oct 6
Primer: Advancements and challenges for deep learning in medical imaging
[Video]
Fall 2021
Oct 6
3KG: Contrastive learning of 12-lead electrocardiograms using physiologically-inspired augmentations
[Video]
Fall 2021
Fall 2021
Date Speaker Title
Sep 29
  • Institute of Computational Biology, Helmholtz Zentrum München

  • Institute of Computational Biology, Helmholtz Zentrum München

Primer: Latent space learning in single cell genomics: Current approaches and challenges
[Video]
Fall 2021
Sep 29
Deep interpretable perturbation modeling in single cell genomics¹; Learning cell communication from spatial graphs of cells²
[Video]
Fall 2021
Sep 22
Visual recognition from one or more images
[Video]
Fall 2021
Sep 22
Representation learning for single-cell, image-based phenotyping
[Video]
Fall 2021
Sep 15 NO MEETING THIS WEEK Fall 2021
Sep 8 No primer Fall 2021
Sep 8
Multimodal single-cell data, open benchmarks, and a NeurIPS 2021 competition (Note: 9am start)
[Video]
Fall 2021
Spring 2021
Date Speaker Title
Jun 2
Primer: Optimal thinning of mcmc output with application to cardiac electrophysiology
[Video]
Spring 2021
Jun 2
  • Depts. of Statistics and Computer Science, Stanford University; Microsoft Research New England

Probabilistic inference and learning with Stein’s method
[Video]
Spring 2021
May 26 NO MEETING THIS WEEK Spring 2021
May 19 NO MEETING THIS WEEK Spring 2021
May 12
  • Bioinformatics and Integrative Genomics Program, Zitnik Lab, Harvard Medical School

Primer: Deep learning for biomedical networks: Methods, challenges, and frontiers
[Video]
Spring 2021
May 12
  • Dept. of Biomedical Informatics, Harvard University; Broad Institute

Actionable machine learning for drug discovery and development
[Video]
Spring 2021
May 5
  • Marks Lab, Harvard Medical School

Primer: Estimation and testing with generative nonparametric Bayesian models
[Video]
Spring 2021
May 5
Building and evaluating generative models of biological sequences, from proteins to whole genomes
[Video]
Spring 2021
Apr 29 No primer Spring 2021
Apr 29
  • Paul G. Allen School of Computer Science and Engineering, University of Washington

Deep learning of immune differentiation (Note: 12pm start)
[Video]
Spring 2021
Apr 28 NO MEETING THIS WEEK Spring 2021
Apr 21 NO MEETING THIS WEEK Spring 2021
Apr 14 NO MEETING THIS WEEK Spring 2021
Spring 2021
Date Speaker Title
Apr 7 No primer Spring 2021
Apr 7
  • Loh Lab, Harvard Medical School; Division of Genetics, Brigham and Women's Hospital; Broad Institute

Imputed repeat polymorphisms point to protein-coding variants driving genetic associations
[Video]
Spring 2021
Mar 31
Primer: Density-aware visualization and sketching of single-cell transcriptomic data
[Video]
Spring 2021
Mar 31
Low dimensional embeddings of words and documents (and how they might apply to single-cell data)
[Video]
Spring 2021
Mar 24
Primer: Generative models of antibodies for functionally optimized library design
[Video]
Spring 2021
Mar 24
Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning
[Video]
Spring 2021
Mar 17 NO MEETING THIS WEEK Spring 2021
Mar 10
  • Center for Communicable Disease Dynamics, Harvard Chan School of Public Health

Primer: Using viral loads and within-host models to improve COVID-19 surveillance
[Video]
Spring 2021
Mar 10
  • Dept. of Statistics, Wharton School, University of Pennsylvania

Simple, flexible and effective pooled testing via hypergraph factorization
[Video]
Spring 2021
Mar 3
Primer: Integrating heterogeneous measurements in single cells
[Video]
Spring 2021
Mar 3
  • Division of Biology and Biological Engineering, California Institute of Technology

Single-cell biology in a software 2.0 world
[Video]
Spring 2021
Feb 24
Primer: Locality sensitive hashing: A sort of history and introduction
[Video]
Spring 2021
Feb 24
Viral diagnostic design with model-based optimization
[Video]
Spring 2021
Feb 17 NO MEETING THIS WEEK Spring 2021
Feb 10 No primer Spring 2021
Feb 10
Bayesian methods for adaptive experimental design
[Video]
Spring 2021
Feb 3 No primer Spring 2021
Feb 3
  • Computational & Systems Biology Program, Memorial Sloan Kettering Cancer Center

The 3D genome and predictive models of gene regulation Spring 2021
Jan 27
  • Depts. Organismic and Evolutionary Biology, Physics, Harvard University

Primer: Genomic investigations of evolutionary dynamics and epistasis in microbial evolution experiments
[Video]
Spring 2021
Jan 27
Predictable patterns in phenotypic evolution
[Video]
Spring 2021
Fall 2020
Date Speaker Title
Fall 2020
Date Speaker Title
Dec 9
Large-scale Bayesian inference for GWAS with coupled Markov chain Monte Carlo
[Video]
Fall 2020
Dec 9
  • Liu Group, Regev Lab, Broad Institute; Dept. of Computational and Systems Biology, Massachusetts Institute of Technology

Determinants of base editing outcomes from target library analysis and machine learning
[Video]
Fall 2020
Dec 2
Primer: Introduction to ecological models for microbiomes
[Video]
Fall 2020
Dec 2
Toward a statistical mechanics of microbiomes
[Video]
Fall 2020
Nov 25 NO MEETING THIS WEEK Fall 2020
Nov 18 No primer Fall 2020
Nov 18
Patterns on pollen: a polysaccharide phase transition process (Note: 11am start)
[Video]
Fall 2020
Nov 11 NO MEETING THIS WEEK Fall 2020
Nov 4 NO MEETING THIS WEEK Fall 2020
Oct 28
Primer: Generalized linear models and latent factor models
[Video]
Fall 2020
Oct 28
  • Dept. of Biostatistics, Harvard University

Inference in generalized bilinear models
[Video]
Fall 2020
Oct 21
Primer: Stochastic gradient-based variational inference
[Video]
Fall 2020
Oct 21
Deep probabilistic programming with Pyro
[Video]
Fall 2020
Oct 14 No primer Fall 2020
Oct 14
  • Dept. of Electrical Engineering and Computer Sciences, Center for Computational Biology, Berkeley AI Research Lab, UC Berkeley; Chan Zuckerberg Biohub

Machine learning-based design of proteins (and small molecules and beyond) (Note: 12pm start)
[Video]
Fall 2020
Oct 7
Primer: Biological sequence design through machine-guided exploration
[Video]
Fall 2020
Oct 7
Machine-guided capsid engineering for gene therapy
[Video]
Fall 2020
Sep 30
  • Research Laboratory of Electronics Computational Cardiovascular Research Group, Massachusetts Institute of Technology

Primer: Modeling cardiovascular physiology
[Video]
Fall 2020
Sep 30
  • Dept. of Electrical Engineering and Computer Science, Institute for Medical Engineering and Science, Computer Science and Artificial Intelligence Laboratory, MIT; Massachusetts General Hospital

Physiology-inspired machine learning models for predicting adverse cardiovascular outcomes
[Video]
Fall 2020
Sep 23
  • Clinical Machine Learning Group, Massachusetts Institute of Technology

Primer: Learning personalized treatment policies from observational data
[Video]
Fall 2020
Fall 2020
Date Speaker Title
Sep 23
  • Dept. of Electrical Engineering and Computer Science, Institute for Medical Engineering & Science, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology

Going beyond diagnosis and prognosis: Machine learning to guide treatment suggestions
[Video]
Fall 2020
Sep 16
Primer: Machines read, humans read: parallels between computer and human representations of meaning (Note: 11am start)
[Video]
Fall 2020
Sep 16
  • Depts. of Computing Science, Psychology, University of Alberta; Canadian Institute for Advanced Research

Decoding word meaning from brain images collected during language production (Note: 12pm start)
[Video]
Fall 2020
Sep 9
  • Broderick Group, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology; ArbiLex

Primer: Gaussian processes: An introduction
[Video]
Fall 2020
Sep 9
  • Dept. of Electrical Engineering and Computer Science, Computer Science and Artificial Intelligence Laboratory, Statistics and Data Science Center, Massachusetts Institute of Technology

Fast discovery of pairwise interactions in high dimensions using Bayes
[Video]
Fall 2020
Spring 2020
Date Speaker Title
May 13
  • TBD

Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
May 13
TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
May 6
  • TBD

Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
May 6
  • Massachusetts Institute of Technology

TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Apr 29
  • Dept. of Mathematics, Lehman College of the City University of New York

Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Apr 29
  • Dept. of Computer Science, Hunter College of the City University of New York

TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Apr 22
  • TBD

Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Apr 22
TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Apr 15 NO MEETING Spring 2020
Apr 8
  • TBD

Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Apr 8
TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Apr 6
Geometric deep learning for functional protein design (Note: Joint CC&E/MIA Special Seminar, Monday at 9:30AM. See abstract for Zoom instructions)
[Video]
Spring 2020
Apr 1
  • Ek Group, Dept. of Computer Science, Technical University of Munich; Siemens AG

Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Apr 1
TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Mar 25 NO MEETING Spring 2020
Spring 2020
Date Speaker Title
Mar 18
  • TBD

Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Mar 18
  • Dept. of Electrical Engineering and Computer Science, Computer Science and Artificial Intelligence Laboratory, Statistics and Data Science Center, Massachusetts Institute of Technology

TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Mar 11
Primer: Biological sequence design through machine-guided exploration (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Mar 11
Machine-guided capsid engineering for gene therapy (NOTE: POSTPONED UNTIL FURTHER NOTICE) Spring 2020
Mar 4
Primer: Only connect: The variety and splendor of neural network architectures Spring 2020
Mar 4
  • Medical and Population Genetics, Broad Institute; Division of Cardiology, Massachusetts General Hospital

Deep learning enables efficient genetic analysis of the human thoracic aorta Spring 2020
Feb 26
  • Neale Lab, Lander Lab, Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital

Primer: The multiple testing problem
[Video]
Spring 2020
Feb 26
  • Paninski Lab, Blei Lab, Dept. of Statistics, Data Science Institute, Columbia University

Smoothed nested testing on directed acyclic graphs
[Video]
Spring 2020
Feb 19 NO MEETING Spring 2020
Feb 12
  • Dept. of Computer Science, University of Toronto; Vector Institute

Primer: Enforcing Lipschitz constraints for neural networks
[Video]
Spring 2020
Feb 12
  • Grosse Group, University of Toronto; Vector Institute

  • Grosse Group, University of Toronto; Vector Institute

Efficient Lipschitz-constrained neural networks
[Video]
Spring 2020
Feb 5
Screening: VAEs & Deep Inverse Modeling (Note: 10-11am in the Auditorium) Spring 2020
Jan 29 No primer Spring 2020
Jan 29 Topics Groups Nucleation Event (10-11am in Monadnock) Spring 2020
Fall 2019
Date Speaker Title
Dec 18
  • Holiday Mixer

Holiday Mixer (Note: 10am in Monadnock) Fall 2019
Dec 6
RNA velocity generalized to transient cell states through dynamical modeling (Note: 2:30-3:30pm in Monadnock)
[Video]
Fall 2019
Dec 4
  • Computer Science & Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology

Primer: An overview of some issues in Bayesian robustness
[Video]
Fall 2019
Dec 4
  • Dept. of Biostatistics, Harvard University; Dana-Farber Cancer Institute; Broad Institute

Using bagged posteriors for robust inference and model criticism
[Video]
Fall 2019
Nov 20
Primer: CellBender remove-background: A deep generative model for unsupervised removal of background noise from scRNA-seq datasets
[Video]
Fall 2019
Nov 20
CellBender droplet-time-machine: Reversing mixed-template cDNA amplification artifacts in droplet-based 3' scRNA-seq assays
[Video]
Fall 2019
Fall 2019
Date Speaker Title
Nov 13
  • CANCELLED

CANCELLED Fall 2019
Nov 8
  • Dept. of Electrical Engineering and Computer Sciences, UC Berkeley

Regev Lab, Cell Circuits and Epigenomics, and MIA special seminar: Deep generative modeling for single-cell transcriptomics (12:30-1:30pm in Monadnock) Fall 2019
Nov 6
Primer: Integrating topological data analysis (TDA) with statistical learning techniques
[Video]
Fall 2019
Nov 6
  • Center for Statistical Sciences, Center for Computational Molecular Biology, Brown University

Statistical pipeline for identifying features that differentiate classes of 3D shapes
[Video]
Fall 2019
Oct 30
Primer: How do we build neural networks we can trust?
[Video]
Fall 2019
Oct 30
Loss valleys, uncertainty, and generalization in deep learning
[Video]
Fall 2019
Oct 23
  • Depts. of Chemistry and Chemical Biology, Physics, Harvard University

Primer: Computational challenges in optical electrophysiology (Note: Auditorium)
[Video]
Fall 2019
Oct 23
New imaging data types and computational challenges at the optical profiling platform (Note: Auditorium)
[Video]
Fall 2019
Oct 22
  • Depts. of Computer Science, Statistical Sciences, University of Toronto

It's time to talk about irregularly-sampled time series (Note: 12-1pm in Serengeti)
[Video]
Fall 2019
Oct 16
  • Dept. of Brain and Cognitive Science, McGovern Institute, Massachusetts Institute of Technology

Primer: Cognitive maps for navigation in the brain
[Video]
Fall 2019
Oct 16
Manifold discovery of cognitive maps
[Video]
Fall 2019
Oct 9
Primer: The geometry of linear regression, privacy-preserving linear algebra, and multi-party GWAS
[Video]
Fall 2019
Oct 9
  • Dept. of Mathematics, Massachusetts Institute of Technology

Key ideas in linear algebra
[Video]
Fall 2019
Oct 2
Primer: Intro to computer vision and its relationship to machine learning
[Video]
Fall 2019
Oct 2
Computer vision for hearts and cells
[Video]
Fall 2019
Sep 25
  • Goldenberg Lab, SickKids Research Institute; Dept. of Computer Science, University of Toronto; Vector Institute

Primer: Learning biological patterns across domains: Investigating and integrating information across data types and sources
[Video]
Fall 2019
Sep 25
  • SickKids Research Institute; Dept. of Computer Science, University of Toronto; Vector Institute

From predicting to explaining biology using machine learning
[Video]
Fall 2019
Sep 18
  • Sunyaev Lab, Dept. of Biomedical Informatics, Harvard Medical School; Division of Genetics, Brigham and Women's Hospital

Primer: DNA damage bypass is a major source of clustered mutations
[Video]
Fall 2019
Sep 18
  • Kharchenko Lab, Dept. of Biomedical Informatics, Harvard Medical School

Population sequencing data reveal a compendium of mutational processes in human germline
[Video]
Fall 2019
Sep 11
  • Ahmed Badran

    Infectious Disease & Microbiome Program, Chemical Biology & Therapeutic Sciences Program, Broad Institute

Primer: Impact of mutagenesis efficiency and selection stringency modulation during continuous directed evolution
[Video]
Fall 2019
Fall 2019
Date Speaker Title
Sep 11
  • Dept. of Biomedical Engineering, UC Irvine

Synthetic genetic systems for rapid mutation and continuous evolution in vivo
[Video]
Fall 2019
Spring 2019
Date Speaker Title
May 29
Interpretable convolutional networks for regulatory genomics
[Video]
Spring 2019
May 22
Primer: Generative models from NLP for sequence data
[Video]
Spring 2019
May 22
  • Dept. of Systems Biology, Harvard Medical School; Broad Institute

Alignment-free models for protein and antibody design
[Video]
Spring 2019
May 15
Primer: Mechanisms for generalized learning across tasks and environments
[Video]
Spring 2019
May 15
  • Depts. of Statistics, Computer Science, Harvard University

Personalized HeartSteps: A reinforcement learning algorithm for optimizing physical activity
[Video]
Spring 2019
May 8
  • Dept. of Systems Biology, Harvard Medical School

Primer: Inference of high-dimensional dynamics
[Video]
Spring 2019
May 8
Lineage tracing on transcriptional landscapes links state to fate during differentiation
[Video]
Spring 2019
May 6
Blind denoising by self-supervision
[Video]
Spring 2019
May 1
  • Dept. of Medicine and Division of Genetics, Brigham and Women's Hospital, Harvard Medical School; Broad Institute

Primer: Hidden Markov models in phasing and imputation
[Video]
Spring 2019
May 1
  • Loh Lab, Dept. of Medicine and Division of Genetics, Brigham and Women's Hospital, Harvard Medical School; Broad Institute

Imputing genomic repeat variants and assessing their phenotypic effects
[Video]
Spring 2019
Apr 24
Primer: Introduction to the tree sequence toolchain
[Video]
Spring 2019
Apr 24
Succinct tree sequences for megasample genomics
[Video]
Spring 2019
Apr 17
  • Galen Ballentine

    Drexel University College of Medicine

Primer: The human brain's default mode network
[Video]
Spring 2019
Apr 17
  • Dept. of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University

Algorithms to understand default brain function
[Video]
Spring 2019
Apr 10
Primer: Extracting causal signal from high-dimensional data: challenges and techniques
[Video]
Spring 2019
Apr 10
  • Rabadan Lab, Dept. of Systems Biology, Data Science Institute, Columbia University

Interpreting and learning from black box models
[Video]
Spring 2019
Apr 3
Primer: Quantifying proteins by mass-spec
[Video]
Spring 2019
Apr 3
Understanding biological systems: In search of direct causal mechanisms
[Video]
Spring 2019
Mar 27
  • Aryee Lab, Zhang Lab; Dana-Farber Cancer Institute, Harvard Medical School, Massachusetts General Hospital

Modeling the 3D organization of chromosomes in the cancer cell nucleus
[Video]
Spring 2019
Spring 2019
Date Speaker Title
Mar 20
Primer: Learning structure in mouse behavior using motion sequenceing (MoSeq)
[Video]
Spring 2019
Mar 20
Using machine learning to understand how the brain implements moment-to-moment action selection
[Video]
Spring 2019
Mar 13
  • Neale Lab, Lander Lab, Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital

Primer: Random matrix theory
[Video]
Spring 2019
Mar 13
Controlling for stratification in (meta-)GWAS with PCA: Theory, applications, and implications
[Video]
Spring 2019
Mar 6
Primer: Generative REgularized ModeLs of proteINs Spring 2019
Mar 6
End-to-end differentiable learning of protein structure
[Video]
Spring 2019
Feb 27
Primer: From Morse theory to geometric ensembling via the topology of PCA
[Video]
Spring 2019
Feb 27
Regularized linear autoencoders, probabilistic PCA, and backpropagation in the brain
[Video]
Spring 2019
Feb 13
Inferring geometric embeddings for single cell data
[Video]
Spring 2019
Feb 13
Optics-free spatio-genetic imaging with DNA microscopy
[Video]
Spring 2019
Feb 6
Primer: Analyzing scientific data with topological data analysis
[Video]
Spring 2019
Feb 6
Using random matrix theory to extract signals from single-cell expression data
[Video]
Spring 2019
Jan 30
  • Talking Machines; Collective Next; Neural Information Processing Systems (neurIPS)

Primer: Super deep generative networks for cat robots: or how I learned to start worrying more about the public conversation
[Video]
Spring 2019
Jan 30
  • Talking Machines; Collective Next; Neural Information Processing Systems (neurIPS)

Group exercise: The story algorithm Spring 2019
Fall 2018
Date Speaker Title
Dec 12
Primer: Challenges in high-dimensional variable selection
[Video]
Fall 2018
Dec 12
Using knockoffs to find important variables with statistical guarantees
[Video]
Fall 2018
Dec 5
  • Massachusetts General Hospital; Harvard Medical School; Broad Institute

  • Pinello Lab, Massachusetts General Hospital (MGH); Joung Lab, MGH, Harvard Medical School; Collins Lab, Massachusetts Institute of Technology

Primer: A deconvolution framework for the analysis of CRISPR tiling screen data
[Video]
Fall 2018
Dec 5
  • Massachusetts General Hospital; Harvard Medical School; Broad Institute

  • Pinello Lab, Massachusetts General Hospital; Harvard Medical School

Single-cell trajectory reconstruction, exploration and mapping from omics data
[Video]
Fall 2018
Nov 14
Primer: Intro to non-negative matrix factorization
[Video]
Fall 2018
Nov 14
  • Sabeti Lab, Dept. of Systems Biology, Harvard Medical School

Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq
[Video]
Fall 2018
Fall 2018
Date Speaker Title
Nov 7
Primer: Intro to topic models
[Video]
Fall 2018
Nov 7
Topic modeling the transcriptional spectrum in innate lymphoid cells
[Video]
Fall 2018
Oct 31
  • Engelhardt Group, Depts. of Computer Science, Quantitative and Computational Biology, Princeton University

Primer: Robust nonlinear manifold learning for single cell RNA-seq data
[Video]
Fall 2018
Oct 31
  • Engelhardt Group, Depts. of Computer Science, Quantitative and Computational Biology, Princeton University

Experimental design for maximizing cell-type discovery in single-cell data
[Video]
Fall 2018
Oct 24
  • Broderick Lab, Machine Learning Group, Massachusetts Institute of Technology; Regev Lab, Broad Institute

  • Florez Lab, Massachusetts General Hospital, Broad Institute

  • Broderick Lab, Computer Science & Artificial Intelligence Lab, Massachusetts Institute of Technology

  • Marks Lab, The Biophysics Graduate Program, Harvard University

Lightning talk social Fall 2018
Oct 24
Studying cell and tissue physiology with random composite experiments
[Video]
Fall 2018
Oct 17
  • Krishnaswamy Lab, Depts. of Genetics, Computer Science, Yale University

Primer: Manifold learning and graph signal processing of high-dimensional, high-throughput biological data
[Video]
Fall 2018
Oct 17
Manifold learning yields insight into cellular state space under complex experimental conditions
[Video]
Fall 2018
Oct 10
  • Computer Science & Artificial Intelligence Lab, Massachusetts Institute of Technology

Biomedical data sharing and analysis with privacy
[Video]
Fall 2018
Oct 3
What might machine learners learn from probabilistic programming?
[Video]
Fall 2018
Sep 26
  • Depts. of Computer Science and Government, Harvard University

Primer: Submodular maximization and machine learning
[Video]
Fall 2018
Sep 26
  • Dept. of Computer Science, Harvard University

Maximizing submodular functions exponentially faster
[Video]
Fall 2018
Sep 19
Primer: Why is deep learning so deep?
[Video]
Fall 2018
Sep 19
Mapping the brain with machine learning
[Video]
Fall 2018
Jul 11
Transcriptomic modeling of chemotherapy side effects using human iPSC-derived cardiomyocytes
[Video]
Fall 2018
Spring 2018
Date Speaker Title
May 23
  • Depts. of Computer Science, University of Copenhagen and IT University of Copenhagen

  • Depts. of Computer Science, University of Copenhagen and IT University of Copenhagen

Primer: Learning from molecular structure
[Video]
Spring 2018
May 23
  • Depts. of Computer Science, University of Copenhagen and IT University of Copenhagen

  • Depts. of Computer Science, University of Copenhagen and IT University of Copenhagen

Convolutional models of molecular structure
[Video]
Spring 2018
May 16
Primer: How philosophy of science can help us better deploy machine learning in biology
[Video]
Spring 2018
May 16
Interpreting sequence models Spring 2018
May 9
  • Depts. of Biomedical Data Science, Computer Science, and Electrical Engineering, Stanford University

Primer: Contrastive PCA
[Video]
Spring 2018
Spring 2018
Date Speaker Title
May 9
  • Depts. of Biomedical Data Science, Computer Science, and Electrical Engineering, Stanford University

AI audit to uncover blind spots of data Spring 2018
May 2
  • Carpenter Lab, Imaging Platform, Broad Institute

  • Carpenter Lab, Imaging Platform, Broad Institute

  • Carpenter Lab, Imaging Platform, Broad Institute

  • Carpenter Lab, Imaging Platform, Broad Institute

How to make a picture worth a thousand numbers: Models and methods in biological image analysis
[Video]
Spring 2018
Apr 25
  • Program for Evolutionary Dynamics, Harvard University

Primer: Hamilton's rule makes no prediction and cannot be tested empirically
[Video]
Spring 2018
Apr 25
  • Program for Evolutionary Dynamics, Harvard University

Evolutionary dynamics
[Video]
Spring 2018
Apr 11
Learning protein structure with a differentiable simulator
[Video]
Spring 2018
Apr 4
  • Center for Genomics and Systems Biology, New York University

Primer: Inference of biological networks with biophysically motivated methods
[Video]
Spring 2018
Apr 4
Multitask learning approaches to biological network inference: linking model estimation across diverse related datasets
[Video]
Spring 2018
Mar 28
Variant filtering and calling with convolutional neural networks
[Video]
Spring 2018
Mar 21
  • Dept. of Mathematics, Emmanuel College; Program for Evolutionary Dynamics, Harvard University

Evolutionary dynamics on any population structure
[Video]
Spring 2018
Mar 7
Inferring microbial phenotypes through latent representations of biological diversity Spring 2018
Feb 28
Primer: Kernel methods and the kernel "trick"
[Video]
Spring 2018
Feb 28
Linking gut microbiomes, genomes and phenotypes via linear mixed models and kernel methods
[Video]
Spring 2018
Feb 21
  • Dept. of Medicine and Division of Genetics, Brigham and Women's Hospital, Harvard Medical School; Broad Institute

  • McCarrol Lab, Broad Institute; Dept. of Genetics, Harvard Medical School

Leveraging long range phasing to detect mosaicism in blood at ultra-low allelic fractions Spring 2018
Feb 14
  • Institute for Medical Engineering & Science, Massachusetts Institute of Technology

Primer: Causal inference
[Video]
Spring 2018
Feb 14
  • Dept. of Electrical Engineering and Computer Science, Institute for Medical Engineering & Science, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology

AI for health needs causality
[Video]
Spring 2018
Feb 7
  • Institute for Medical Engineering and Science, Dept. of Civil and Environmental Engineering, Massachusetts Institute of Technology

Rapid bacterial adaptation within individual human microbiomes Spring 2018
Fall 2017
Date Speaker Title
Dec 13
  • Dept. of Biomedical Informatics, Harvard Medical School; Dept. of Biostatistics and Computational Biology, Dana-Farber Cancer Institute

  • Harvard Medical School; Dana-Farber Cancer Institute

In search of lost time: Reconstructing the evolutionary history of cancer genomes
[Video]
Fall 2017
Dec 6
  • Troyanskaya Lab, Lewis-Sigler Institute for Integrative Genomics, Princeton University

Primer: Integrated, tissue-specific analysis of biological data
[Video]
Fall 2017
Dec 6
  • Lewis-Sigler Institute for Integrative Genomics, Princeton University; Center for Computational Biology, Flatiron Institute

From genome to networks: A data-driven, tissue-specific view of human disease Fall 2017
Nov 29
Primer: Introduction to Hi-C Fall 2017
Fall 2017
Date Speaker Title
Nov 29
  • Center for Genomic Architecture, Baylor College of Medicine; Depts. of Computational and Applied Mathematics and Computer Science, Rice University

A 3D Code in the human genome Fall 2017
Nov 15
Machine-learning-based CRISPR guide design
[Video]
Fall 2017
Nov 8
Automated Machine Learning
[Video]
Fall 2017
Nov 1
  • Dept. of Mathematics, Massachusetts Institute of Technology

Message passing algorithms for cryo-EM and synchronization
[Video]
Fall 2017
Oct 25
  • MIT CSAIL, HMS, Harvard CS

  • Dept. of Computer Science, Harvard University; Harvard/MIT MD-PhD Program, Harvard Medical School

Primer: Hypothesis testing and measures of dependence
[Video]
Fall 2017
Oct 25
  • MIT CSAIL, HMS, Harvard CS

  • Dept. of Computer Science, Harvard University; Harvard/MIT MD-PhD Program, Harvard Medical School

Detecting novel associations in large data sets
[Video]
Fall 2017
Oct 11
  • Michael Rooney

    Neon Therapeutics

Primer: Intro to tumor immunity
[Video]
Fall 2017
Oct 11
Improving endogenous antigen prediction to support personalized cancer vaccine development
[Video]
Fall 2017
Oct 4
Insight into the biology of common diseases using summary statistics of large genome-wide association studies
[Video]
Fall 2017
Sep 27
Primer: A tutorial on optimal transport
[Video]
Fall 2017
Sep 27
  • Broad Institute; Statistics and Data Science Center, Massachusetts Institute of Technology

Learning developmental landscapes from single-cell gene expression with optimal transport
[Video]
Fall 2017
Sep 20
Learning phylogeny through f-statistics
[Video]
Fall 2017
Sep 13
  • Finucane Lab, Broad Institute

Primer: Generalized least squares
[Video]
Fall 2017
Sep 13
  • Dept. of Computer Science, Harvard University; Harvard/MIT MD-PhD Program, Harvard Medical School

Detecting effects of transcription factors on disease
[Video]
Fall 2017
Sep 6
Primer: Classifying genomic sequences with convolutional neural networks
[Video]
Fall 2017
Sep 6
Reading the rules of gene regulation from the human noncoding genome
[Video]
Fall 2017
Fall 2016
Date Speaker Title
Dec 14
What is a compiler?
[Video]
Fall 2016
Dec 14
  • The Programming Languages Group, Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS)

Compiling probabilistic programs
[Video]
Fall 2016
Dec 7
Mass spectrometry-based proteomics
[Video]
Fall 2016
Dec 7
Spectral unmixing for next-generation mass spectrometry proteomics
[Video]
Fall 2016
Fall 2016
Date Speaker Title
Nov 16
Practical recommendations for training convolutional neural nets
[Video]
Fall 2016
Nov 16
Deep learning for computational pathology
[Video]
Fall 2016
Nov 9
Dirichlet processes
[Video]
Fall 2016
Nov 9
  • Donnelly Centre for Cellular and Biomedical Research, Depts. of Molecular Genetics, Computer Science, and Electrical and Computer Engineering, University of Toronto

Algorithms for reconstructing tumor evolution
[Video]
Fall 2016
Nov 2
  • Depts. of Genetics and Computer Science, Stanford University

Integrative, interpretable deep learning frameworks for regulatory genomics and epigenomics
[Video]
Fall 2016
Oct 26
Automatic differentiation, the algorithm behind all deep neural networks
[Video]
Fall 2016
Oct 26
  • Churchman Lab, Harvard Medical School

FIDDLE: An integrative deep learning framework for functional genomic data inference
[Video]
Fall 2016
Oct 12
Topological data analysis: What is persistent homology?
[Video]
Fall 2016
Oct 12
  • Dept. of Mathematics, Warren Center for Network and Data Sciences, University of Pennsylvania

Topological data analysis: What can persistent homology see?
[Video]
Fall 2016
Sep 28
  • Dept. of Systems Biology, Harvard University; Harvard-MIT Health Sciences and Technology

Experimental and computational techniques underlying RNA-seq
[Video]
Fall 2016
Sep 28
  • Dept. of Data Sciences, Dana-Farber Cancer Institute; Dept. of Biostatistics, Harvard School Public Health

Overcoming bias and batch effects in high-throughput data
[Video]
Fall 2016
Sep 21
Probabilistic generative models and posterior inference
[Video]
Fall 2016
Sep 21
Automated inference and the promise of probabilistic programming
[Video]
Fall 2016
Sep 14
  • Regev Lab, Lander Lab, Broad Institute; Dept. of Computational and Systems Biology, Massachusetts Institute of Technology

Composite measurements and molecular compressed sensing for efficient transcriptomics at scale
[Video]
Fall 2016
Sep 14
  • Hail Team, Neale Lab, Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital

Introduction to compressed sensing Fall 2016
Spring 2016
Date Speaker Title
Jun 1
  • Depts. of Genome Sciences, Electrical Engineering, and Computer Science, University of Washington

Identifying molecular markers for cancer treatment from big data Spring 2016
May 25
MIA Breakfast Social Spring 2016
May 18
Basic introduction to distributed computation
[Video]
Spring 2016
May 18
  • Dept. of Electrical Engineering and Computer Science, Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology; Databricks

Scaling data analysis with Apache Spark
[Video]
Spring 2016
May 11
Variational Bayesian inference
[Video]
Spring 2016
Spring 2016
Date Speaker Title
May 11
  • Depts. of Statistics and Computer Science, Data Science Institute, Columbia University

Scaling and generalizing variational inference
[Video]
Spring 2016
May 4
  • Harvard Intelligent Probabilistic Systems, Harvard University; Harvard Medical School; Massachusetts Institute of Technology

Gaussian processes
[Video]
Spring 2016
May 4
Bayesian structured sparsity: Rethinking sparse regression
[Video]
Spring 2016
Apr 27
  • Genetic Perturbation Platform, Broad Institute

Linear codes
[Video]
Spring 2016
Apr 27
  • Dept. of Computer Science, Columbia University; NY Genome Center

Compressed experiments
[Video]
Spring 2016
Apr 27
  • Dept. of Electrical Engineering, Stanford University; Dept. of Electrical Engineering and Computer Sciences, UC Berkeley

The science of information: Case studies from DNA and RNA assembly
[Video]
Spring 2016
Apr 20
  • Daly Lab, Massachusetts General Hospital; Broad Institute

Multiple testing and false discovery rate Spring 2016
Apr 20
DNA microscopy and the sequence-to-image inverse problem Spring 2016
Apr 13
t-dist. stochastic neighbor embedding (t-SNE) Spring 2016
Apr 13
Information in cell images: Targeting diseases and characterizing compounds Spring 2016
Apr 6
  • Rinn Lab, Dept. of Stem Cell and Regenerative Biology, Harvard University

Convolutional neural nets Spring 2016
Apr 6
AtomNet: a deep convolutional neural net for bioactivity prediction in structure-based drug discovery Spring 2016
Mar 30
  • Dept. of Mathematics, Massachusetts Institute of Technology

Non-negative matrix factorization (NMF) Spring 2016
Mar 30
  • Dept. of Organismic and Evolutionary Biology, Harvard University

The effects of population pedigrees on gene genealogies Spring 2016
Mar 23
Linear models III: regularization, LASSO and sparsity Spring 2016
Mar 23
  • Google Brain, Google Research Cambridge

A quick introduction to TensorFlow and related API's Spring 2016
Mar 16
  • Harvard Intelligent Probabilistic Systems, Harvard University; Harvard Medical School; Massachusetts Institute of Technology

Linear models II: Regularization and ridge Spring 2016
Mar 16
  • Janelia Research Campus; Howard Hughes Medical Institute

Open source tools for large-scale neuroscience
[Video]
Spring 2016
Mar 9
  • Price Lab, Harvard School of Public Health; Dept. of Mathematics, Massachusetts Institute of Technology

Linear models I: Ordinary least squares Spring 2016
Mar 9
  • Price Lab, Harvard School of Public Health

Haplotype phasing in large cohorts: Modeling, search, or both? Spring 2016
Spring 2016
Date Speaker Title
Mar 2
  • McCarrol Lab, Broad Institute; Dept. of Genetics, Harvard Medical School

Hidden Markov models II Spring 2016
Mar 2
  • Dept. of Physics, Institute for Medical Engineering and Science, Massachusetts Institute of Technology

Polymer models of chromosomes Spring 2016
Feb 24
  • McCarrol Lab, Broad Institute; Dept. of Genetics, Harvard Medical School

Hidden Markov models I Spring 2016
Feb 24
Sparse inverse problems Spring 2016
Feb 17
  • Hail Team, Neale Lab, Broad Institute; Dept. of Mathematics, Massachusetts Institute of Technology

Frequentist vs Bayesian inference Spring 2016
Feb 17
  • Dept. of Electrical Engineering and Computer Science, Institute for Data, Systems and Society (IDSS), Massachusetts Institute of Technology

Gene regulation in space and time
[Video]
Spring 2016
Feb 10
Primer: Principal component analysis (PCA) Spring 2016
Feb 10
Systems biology: Can mathematics lead experiments? Spring 2016
Feb 3
  • Dept. of Biomedical Informatics, Harvard University; Brigham and Women's Hospital; Broad Institute

Judging the importance of human mutations using evolutionary models Spring 2016
Jan 27
  • Depts. of Electrical and Computer Engineering, Computer Science, and Medical Research, University of Toronto; Deep Genomics

Genomic medicine: Will software eat bio? Spring 2016
Fall 2015
Date Speaker Title
Nov 30
  • Datta Lab, Harvard Intelligent Probabilistic Systems, Harvard University

TS II. Modeling structure in time series Fall 2015
Nov 23
  • Datta Lab, Harvard Intelligent Probabilistic Systems, Harvard University; Twitter

TS I. Mapping sub-second structure in mouse behavior Fall 2015
Nov 16
  • Rinn Lab, Dept. of Stem Cell and Regenerative Biology, Harvard University

Harvard Stem Cell NN III. Learning the regulatory code of the accessible genome with deep convolutional neural nets Fall 2015
Nov 12
  • The Original HIPSter, Twitter Cortex, Talking Machines

Machine learning and the life sciences: Beyond data analysis
[Video]
Fall 2015
Nov 9
  • Harvard Intelligent Probabilistic Systems, Harvard University

NN II. Convolutional networks on graphs for learning molecular fingerprints Fall 2015
Nov 2
  • Harvard Intelligent Probabilistic Systems, Harvard University

NN I. Reverse-mode differentiation and autograd Fall 2015
Oct 19
  • Harvard Intelligent Probabilistic Systems, Harvard University

DM II. Discrete models with continuous latent structure: A new hope Fall 2015
Oct 13
DM I. Bayesian logistic regression and mixed models: Revenge of the Gibbs Fall 2015
Sep 21
  • Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital

CS2: Compressed sensing Fall 2015
Sep 21
  • Dept. of Earth and Planetary Sciences, Harvard University; Google Research

CS1: Exploiting sparse and quantized signals to solve linear systems Fall 2015
Fall 2015
Date Speaker Title
Sep 14
Quantifying protein isoforms Fall 2015
Summer 2015
Date Speaker Title
Jul 27
  • Broad Institute; Harvard Medical School; Massachusetts General Hospital

Challenges in normalization of RNAseq data Summer 2015
Jul 20
LD score regression for distinguishing confounding from polygenicity Summer 2015
Jul 13
  • Mark Flaherty

    Data Sciences Platform, Broad Institute

Introduction to evolutionary algorithms and NEAT Summer 2015
Jul 6
The Chinese restaurant process and Indian buffet process Summer 2015
Jun 29
Introduction to Dirichlet processes Summer 2015
Jun 22
Conjugate priors and Hardy-Weinberg equilibrium (Bishop, Ch2) Summer 2015
Jun 15
Discussion of Pachter's p-value prize Summer 2015
Jun 8
Choosing priors in Bayesian inference Summer 2015
Jun 1
Graph-based genetic sequence representation Summer 2015
Spring 2015
Date Speaker Title
May 4
Introduction to Gaussian processes and Bayesian optimization (Bishop, Ch6) Spring 2015
Apr 28
Connectivity map and challenges in data normalization Spring 2015
Apr 14
Linear mixed models for genetic association analysis Spring 2015
Apr 7
Genetic fingerprints and contamination estimation Spring 2015
Mar 30
Markov Chain Monte Carlo and Gibbs sampling on Gaussian mixture models (Bishop, Ch11) Spring 2015
Mar 23
Variant quality score recalibration Spring 2015
Mar 16
  • Dept. of Mathematics, Massachusetts Institute of Technology

Variational Bayes and inference on Gaussian mixture models (Bishop, Ch10) Spring 2015
Mar 9
  • Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute

Expectation maximization and inference on Gaussian mixture models (Bishop, Ch9) Spring 2015
Mar 2
  • Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute

Introduction to Bayesian graphical models: the Gaussian mixture model (Bishop, Ch8) Spring 2015
Feb 24
  • Dept. of Mathematics, Harvard University

  • Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute

  • Broad Institute

  • Dept. of Mathematics, Massachusetts Institute of Technology

Comparison of dimensional reduction methods: PCA, ICA, NMF, tSNE, and diffusion maps Spring 2015
Spring 2015
Date Speaker Title
Jan 26
Independent component analysis (ICA) and projection pursuit Spring 2015
Fall 2014
Date Speaker Title
Dec 15
  • Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute

  • Dept. of Mathematics, Massachusetts Institute of Technology

Non-linear dimensional reduction: tSNE and diffusion maps Fall 2014
Dec 8
Non-negative matrix factorization (NMF) Fall 2014
Nov 24
Principle component analysis (PCA) and the Marchenko-Pastur law Fall 2014
Nov 3
  • Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute

  • Broad Institute

Puzzle day: Drunk Monty Hall, the two envelopes, the bloody crime scene, and Simpson's paradox Fall 2014
Oct 27
  • Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute

Optimal coverage in rare variant association studies Fall 2014
Oct 20
Detecting sample swap Fall 2014
Oct 6
Contingency tables III: Examples in genetics Fall 2014
Sep 29
Contingency tables II: Correlation, Pearson chi-squared test, and Fisher exact test Fall 2014
Sep 22
Contingency tables I: t-test and z-test Fall 2014