MIA Talks Search

Fall 2020
Date	Speaker	Affiliations	Title
Dec 9			Primer: TBD
Dec 9	Gloriia Novikova	Goate Lab, Icahn School of Medicine at Mount Sinai	TBD
Dec 2			Primer: TBD
Dec 2	Pankaj Mehta	Dept. of Physics, Boston University	TBD
Nov 25			NO MEETING THIS WEEK
Nov 18			Primer: TBD
Nov 18	Asja Radja	Mahadevan Group, Harvard University	TBD
Nov 11			NO MEETING THIS WEEK
Nov 4			NO MEETING THIS WEEK
Oct 28	Will Townes	Engelhardt Group, Princeton University	Primer: Generalized linear models and latent factor models
Oct 28	Jeff Miller	Dept. of Biostatistics, Harvard University	Inference in generalized bilinear models
Oct 21	Eli Bingham	Pyro team, Broad Institute	Primer: Stochastic gradient-based variational inference
Oct 21	Fritz Obermeyer	Pyro team, Broad Institute	Deep probabilistic programming with Pyro
Oct 14			No primer
Oct 14	Jennifer Listgarten [Video]	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)
Oct 7	Sam Sinai [Video]	Dyno Therapeutics	Primer: Biological sequence design through machine-guided exploration
Oct 7	Eric Kelsic [Video]	Dyno Therapeutics	Machine-guided capsid engineering for gene therapy
Sep 30	Daphne Schlesinger [Video]	Research Laboratory of Electronics Computational Cardiovascular Research Group, Massachusetts Institute of Technology	Primer: Modeling cardiovascular physiology
Sep 30	Collin Stultz [Video]	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
Sep 23	Mike Oberst	Clinical Machine Learning Group, Massachusetts Institute of Technology	Primer: Learning personalized treatment policies from observational data

Fall 2020
Date	Speaker	Affiliations	Title
Sep 23	David Sontag	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
Sep 16	Rohan Saha [Video]	University of Alberta	Primer: Machines read, humans read: parallels between computer and human representations of meaning (Note: 11am start)
Sep 16	Alona Fyshe [Video]	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)
Sep 9	Raj Agrawal [Video]	Broderick Group, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology; ArbiLex	Primer: Gaussian processes: An introduction
Sep 9	Tamara Broderick [Video]	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

Spring 2020
Date	Speaker	Affiliations	Title
May 20			NO MEETING, SEE YOU NEXT SEMESTER!
May 13	TBD		Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
May 13	Hayden Metsky	Sabeti Lab, Broad Institute	TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
May 6	TBD		Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
May 6	Max Shen	Massachusetts Institute of Technology	TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Apr 29	Megan Owen	Dept. of Mathematics, Lehman College of the City University of New York	Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Apr 29	Katherine St. John	Dept. of Computer Science, Hunter College of the City University of New York	TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Apr 22	TBD		Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Apr 22	Fritz Obermeyer	Uber AI; Pyro	TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Apr 15			NO MEETING
Apr 8	TBD		Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Apr 8	Pankaj Mehta	Dept. of Physics, Boston University	TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Apr 6	Michael Bronstein [Video]	Dept. of Computing, Imperial College London; Twitter	Geometric deep learning for functional protein design (Note: Joint CC&E/MIA Special Seminar, Monday at 9:30AM. See abstract for Zoom instructions)
Apr 1	Markus Kaiser	Ek Group, Dept. of Computer Science, Technical University of Munich; Siemens AG	Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Apr 1	Carl Henrik Ek	Dept. of Computer Science, University of Bristol	TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)

Spring 2020
Date	Speaker	Affiliations	Title
Mar 25			NO MEETING
Mar 18	TBD		Primer: TBD (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Mar 18	Tamara Broderick	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)
Mar 11	Sam Sinai	Dyno Therapeutics	Primer: Biological sequence design through machine-guided exploration (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Mar 11	Eric Kelsic	Dyno Therapeutics	Machine-guided capsid engineering for gene therapy (NOTE: POSTPONED UNTIL FURTHER NOTICE)
Mar 4	Sam Friedman	Data Sciences Platform, Broad Institute	Primer: Only connect: The variety and splendor of neural network architectures
Mar 4	James Pirruccello	Medical and Population Genetics, Broad Institute; Division of Cardiology, Massachusetts General Hospital	Deep learning enables efficient genetic analysis of the human thoracic aorta
Feb 26	Alex Bloemendal [Video]	Neale Lab, Lander Lab, Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital	Primer: The multiple testing problem
Feb 26	Jackson Loper [Video]	Paninski Lab, Blei Lab, Dept. of Statistics, Data Science Institute, Columbia University	Smoothed nested testing on directed acyclic graphs
Feb 19			NO MEETING
Feb 12	Roger Grosse [Video]	Dept. of Computer Science, University of Toronto; Vector Institute	Primer: Enforcing Lipschitz constraints for neural networks
Feb 12	Cem Anil James Lucas [Video]	Grosse Group, University of Toronto; Vector Institute Grosse Group, University of Toronto; Vector Institute	Efficient Lipschitz-constrained neural networks
Feb 5	Max Welling (recording) Ray Jones	University of Amsterdam; Qualcomm Technologies; Canadian Institute for Advanced Research Lander Lab, Broad Institute	Screening: VAEs & Deep Inverse Modeling (Note: 10-11am in the Auditorium)
Jan 29			No primer
Jan 29	Aleksandrina Goeva Gopal Sarma Daniel King Patrick Schultz Alex Bloemendal Hilary Finucane Samuel Friedman		Topics Groups Nucleation Event (10-11am in Monadnock)

Fall 2019
Date	Speaker	Affiliations	Title
Dec 18	Holiday Mixer		Holiday Mixer (Note: 10am in Monadnock)
Dec 6	Volker Bergen [Video]	Theis Lab, Institute of Computational Biology	RNA velocity generalized to transient cell states through dynamical modeling (Note: 2:30-3:30pm in Monadnock)
Dec 4	Will Stephenson [Video]	Computer Science & Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology	Primer: An overview of some issues in Bayesian robustness
Dec 4	Jonathan Huggins [Video]	Dept. of Biostatistics, Harvard University; Dana-Farber Cancer Institute; Broad Institute	Using bagged posteriors for robust inference and model criticism
Nov 20	Stephen Fleming [Video]	Data Sciences Platform, Broad Institute	Primer: CellBender remove-background: A deep generative model for unsupervised removal of background noise from scRNA-seq datasets

Fall 2019
Date	Speaker	Affiliations	Title
Nov 20	Mehrtash Babadi [Video]	Data Sciences Platform, Broad Institute	CellBender droplet-time-machine: Reversing mixed-template cDNA amplification artifacts in droplet-based 3' scRNA-seq assays
Nov 13	CANCELLED		CANCELLED
Nov 13	CANCELLED		CANCELLED
Nov 8	Romain Lopez	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)
Nov 6	Emily Winn [Video]	Crawford Lab, Brown University	Primer: Integrating topological data analysis (TDA) with statistical learning techniques
Nov 6	Lorin Crawford [Video]	Center for Statistical Sciences, Center for Computational Molecular Biology, Brown University	Statistical pipeline for identifying features that differentiate classes of 3D shapes
Oct 30	Pavel Izmailov Polina Kirichenko [Video]	Courant Institute, New York University Courant Institute, New York University	Primer: How do we build neural networks we can trust?
Oct 30	Andrew Gordon Wilson [Video]	Courant Institute, New York University	Loss valleys, uncertainty, and generalization in deep learning
Oct 23	Adam Cohen [Video]	Depts. of Chemistry and Chemical Biology, Physics, Harvard University	Primer: Computational challenges in optical electrophysiology (Note: Auditorium)
Oct 23	Sami Farhi [Video]	Regev Lab, Broad Institute	New imaging data types and computational challenges at the optical profiling platform (Note: Auditorium)
Oct 22	David Duvenaud [Video]	Depts. of Computer Science, Statistical Sciences, University of Toronto	It's time to talk about irregularly-sampled time series (Note: 12-1pm in Serengeti)
Oct 16	Ila Fiete [Video]	Dept. of Brain and Cognitive Science, McGovern Institute, Massachusetts Institute of Technology	Primer: Cognitive maps for navigation in the brain
Oct 16	Sam Lewallen [Video]	Center for Brain Science, Harvard University	Manifold discovery of cognitive maps
Oct 9	Jon Bloom Hoon Cho [Video]	Hail Team, Neale Lab, Broad Institute Broad Institute	Primer: The geometry of linear regression, privacy-preserving linear algebra, and multi-party GWAS
Oct 9	Gil Strang [Video]	Dept. of Mathematics, Massachusetts Institute of Technology	Key ideas in linear algebra
Oct 2	Allen Goodman [Video]	Carpenter Lab, Imaging Platform, Broad Institute	Primer: Intro to computer vision and its relationship to machine learning
Oct 2	Sam Friedman Gregory Way Beth Cimini [Video]	Data Sciences Platform, Broad Institute Carpenter Lab, Imaging Platform, Broad Institute Carpenter Lab, Imaging Platform, Broad Institute	Computer vision for hearts and cells
Sep 25	Lauren Erdman [Video]	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
Sep 25	Anna Goldenberg [Video]	SickKids Research Institute; Dept. of Computer Science, University of Toronto; Vector Institute	From predicting to explaining biology using machine learning
Sep 18	Vova (Vladimir) Seplyarskiy [Video]	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

Fall 2019
Date	Speaker	Affiliations	Title
Sep 18	Ruslan Soldatov [Video]	Kharchenko Lab, Dept. of Biomedical Informatics, Harvard Medical School	Population sequencing data reveal a compendium of mutational processes in human germline
Sep 11	Ahmed Badran [Video]	Infectious Disease & Microbiome Program, Chemical Biology & Therapeutic Sciences Program, Broad Institute	Primer: Impact of mutagenesis efficiency and selection stringency modulation during continuous directed evolution
Sep 11	Chang Liu [Video]	Dept. of Biomedical Engineering, UC Irvine	Synthetic genetic systems for rapid mutation and continuous evolution in vivo

Spring 2019
Date	Speaker	Affiliations	Title
May 29	Peter Koo [Video]	Eddy Lab, Harvard University	Interpretable convolutional networks for regulatory genomics
May 22	Aaron Kollasch [Video]	Marks Lab, Harvard Medical School, Broad Institute	Primer: Generative models from NLP for sequence data
May 22	Debora Marks [Video]	Dept. of Systems Biology, Harvard Medical School; Broad Institute	Alignment-free models for protein and antibody design
May 15	Natasha Jaques [Video]	MIT Media Lab, Massachusetts Institute of Technology	Primer: Mechanisms for generalized learning across tasks and environments
May 15	Susan Murphy [Video]	Depts. of Statistics, Computer Science, Harvard University	Personalized HeartSteps: A reinforcement learning algorithm for optimizing physical activity
May 8	Allon Klein [Video]	Dept. of Systems Biology, Harvard Medical School	Primer: Inference of high-dimensional dynamics
May 8	Caleb Weinreb [Video]	Dept. of Systems Biology, Harvard Medical School	Lineage tracing on transcriptional landscapes links state to fate during differentiation
May 6	Joshua Batson [Video]	Chan Zuckerberg Biohub	Blind denoising by self-supervision
May 1	Po-Ru Loh [Video]	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
May 1	Ronen Mukamel [Video]	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
Apr 24	Wilder Wohns [Video]	Dept. of Statistics, University of Oxford	Primer: Introduction to the tree sequence toolchain
Apr 24	Jerome Kelleher [Video]	Big Data Institute, University of Oxford	Succinct tree sequences for megasample genomics
Apr 17	Galen Ballentine [Video]	Drexel University College of Medicine	Primer: The human brain's default mode network
Apr 17	Danilo Bzdok [Video]	Dept. of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University	Algorithms to understand default brain function
Apr 10	Alexander D'Amour [Video]	Google Brain	Primer: Extracting causal signal from high-dimensional data: challenges and techniques
Apr 10	Wesley Tansey [Video]	Rabadan Lab, Dept. of Systems Biology, Data Science Institute, Columbia University	Interpreting and learning from black box models
Apr 3	Harrison Specht [Video]	Slavov Lab, Northeastern University	Primer: Quantifying proteins by mass-spec

Spring 2019
Date	Speaker	Affiliations	Title
Apr 3	Nikolai Slavov [Video]	Dept. of Bioengineering, Northeastern University	Understanding biological systems: In search of direct causal mechanisms
Mar 27	Alejandro Reyes [Video]	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
Mar 20	Ralph Peterson [Video]	Datta Lab, Harvard Medical School	Primer: Learning structure in mouse behavior using motion sequenceing (MoSeq)
Mar 20	Jeffrey Markowitz [Video]	Datta Lab, Sabatini Lab, Harvard Medical School	Using machine learning to understand how the brain implements moment-to-moment action selection
Mar 13	Alex Bloemendal [Video]	Neale Lab, Lander Lab, Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital	Primer: Random matrix theory
Mar 13	Christina Chen [Video]	Neale Lab, Broad Institute	Controlling for stratification in (meta-)GWAS with PCA: Theory, applications, and implications
Mar 6	Sergey Ovchinnikov	Harvard University	Primer: Generative REgularized ModeLs of proteINs
Mar 6	Mohammed AlQuraishi [Video]	Harvard Medical School	End-to-end differentiable learning of protein structure
Feb 27	Cotton Seed Jon Bloom [Video]	Hail Team, Neale Lab, Broad Institute Hail Team, Neale Lab, Broad Institute	Primer: From Morse theory to geometric ensembling via the topology of PCA
Feb 27	Daniel Kunin Aleksandrina Goeva [Video]	Stanford University Macosko Lab, Broad Institute	Regularized linear autoencoders, probabilistic PCA, and backpropagation in the brain
Feb 13	Mor Nitzan [Video]	Harvard University	Inferring geometric embeddings for single cell data
Feb 13	Joshua Weinstein [Video]	Zhang Lab, Regev Lab, Broad Institute	Optics-free spatio-genetic imaging with DNA microscopy
Feb 6	Andrew J. Blumberg [Video]	Dept. of Mathematics, University of Texas at Austin	Primer: Analyzing scientific data with topological data analysis
Feb 6	Andrew J. Blumberg [Video]	Dept. of Mathematics, University of Texas at Austin	Using random matrix theory to extract signals from single-cell expression data
Jan 30	Katherine Gorman [Video]	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
Jan 30	Katherine Gorman	Talking Machines; Collective Next; Neural Information Processing Systems (neurIPS)	Group exercise: The story algorithm

Fall 2018
Date	Speaker	Affiliations	Title
Dec 12	Wenshuo Wang [Video]	Dept. of Statistics, Harvard University	Primer: Challenges in high-dimensional variable selection
Dec 12	Lucas Janson [Video]	Dept. of Statistics, Harvard University	Using knockoffs to find important variables with statistical guarantees
Dec 5	Luca Pinello Jonathan Hsu [Video]	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
Dec 5	Luca Pinello Huidong Chen [Video]	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

Fall 2018
Date	Speaker	Affiliations	Title
Nov 14	Aleksandrina Goeva [Video]	Macosko Lab, Broad Institute	Primer: Intro to non-negative matrix factorization
Nov 14	Dylan Kotliar [Video]	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
Nov 7	David Benjamin [Video]	Data Sciences Platform, Broad Institute	Primer: Intro to topic models
Nov 7	Samantha Riesenfeld [Video]	Regev Lab, Broad Institute; Kuchroo Lab, Harvard Medical School	Topic modeling the transcriptional spectrum in innate lymphoid cells
Oct 31	Archit Verma [Video]	Engelhardt Group, Depts. of Computer Science, Quantitative and Computational Biology, Princeton University	Primer: Robust nonlinear manifold learning for single cell RNA-seq data
Oct 31	Bianca Dumitrascu [Video]	Engelhardt Group, Depts. of Computer Science, Quantitative and Computational Biology, Princeton University	Experimental design for maximizing cell-type discovery in single-cell data
Oct 24	Miriam Shiffman Miriam Udler Brian Trippe Eli Weinstein	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
Oct 24	Brian Cleary [Video]	Regev Lab, Lander Lab, Broad Institute	Studying cell and tissue physiology with random composite experiments
Oct 17	David van Dijk [Video]	Krishnaswamy Lab, Depts. of Genetics, Computer Science, Yale University	Primer: Manifold learning and graph signal processing of high-dimensional, high-throughput biological data
Oct 17	Smita Krishnaswamy [Video]	Depts. of Genetics, Computer Science, Yale University	Manifold learning yields insight into cellular state space under complex experimental conditions
Oct 10	Hoon Cho [Video]	Computer Science & Artificial Intelligence Lab, Massachusetts Institute of Technology	Biomedical data sharing and analysis with privacy
Oct 3	Dustin Tran Chris Suter [Video]	Google Brain Google Brain	What might machine learners learn from probabilistic programming?
Sep 26	Adam Breuer [Video]	Depts. of Computer Science and Government, Harvard University	Primer: Submodular maximization and machine learning
Sep 26	Yaron Singer [Video]	Dept. of Computer Science, Harvard University	Maximizing submodular functions exponentially faster
Sep 19	David Rolnick [Video]	University of Pennsylvania	Primer: Why is deep learning so deep?
Sep 19	David Rolnick [Video]	University of Pennsylvania	Mapping the brain with machine learning
Jul 11	David Knowles [Video]	Stanford Medicine	Transcriptomic modeling of chemotherapy side effects using human iPSC-derived cardiomyocytes

Spring 2018
Date	Speaker	Affiliations	Title
May 23	Wouter Boomsma Jes Frellsen [Video]	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
May 23	Wouter Boomsma Jes Frellsen [Video]	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
May 16	Larson Hogstrom [Video]	Lander Lab, Broad Institute	Primer: How philosophy of science can help us better deploy machine learning in biology

Spring 2018
Date	Speaker	Affiliations	Title
May 16	Ray Jones	Lander Lab, Broad	Interpreting sequence models
May 9	James Zou [Video]	Depts. of Biomedical Data Science, Computer Science, and Electrical Engineering, Stanford University	Primer: Contrastive PCA
May 9	James Zou	Depts. of Biomedical Data Science, Computer Science, and Electrical Engineering, Stanford University	AI audit to uncover blind spots of data
May 2	Shantanu Singh Jane Hung Juan Caicedo Mohammad Rohban [Video]	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
Apr 25	Martin Nowak [Video]	Program for Evolutionary Dynamics, Harvard University	Primer: Hamilton's rule makes no prediction and cannot be tested empirically
Apr 25	Martin Nowak [Video]	Program for Evolutionary Dynamics, Harvard University	Evolutionary dynamics
Apr 11	John Ingraham [Video]	Marks Lab, Harvard Medical School	Learning protein structure with a differentiable simulator
Apr 4	Rich Bonneau [Video]	Center for Genomics and Systems Biology, New York University	Primer: Inference of biological networks with biophysically motivated methods
Apr 4	Dayanne Castro [Video]	Bonneau Lab, New York University	Multitask learning approaches to biological network inference: linking model estimation across diverse related datasets
Mar 28	Samuel Friedman [Video]	Data Sciences Platform, Broad Institute	Variant filtering and calling with convolutional neural networks
Mar 21	Ben Allen [Video]	Dept. of Mathematics, Emmanuel College; Program for Evolutionary Dynamics, Harvard University	Evolutionary dynamics on any population structure
Mar 7	Jacob Oppenheim	Indigo Agriculture	Inferring microbial phenotypes through latent representations of biological diversity
Feb 28	Ray Jones [Video]	Lander Lab, Broad Institute	Primer: Kernel methods and the kernel "trick"
Feb 28	Omer Weissbrod [Video]	Price Group, Harvard School of Public Health	Linking gut microbiomes, genomes and phenotypes via linear mixed models and kernel methods
Feb 21	Po-Ru Loh Giulio Genovese	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
Feb 14	Fredrik Johansson [Video]	Institute for Medical Engineering & Science, Massachusetts Institute of Technology	Primer: Causal inference
Feb 14	David Sontag [Video]	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
Feb 7	Tami Lieberman	Institute for Medical Engineering and Science, Dept. of Civil and Environmental Engineering, Massachusetts Institute of Technology	Rapid bacterial adaptation within individual human microbiomes

Fall 2017
Date	Speaker	Affiliations	Title
Dec 13	Cheng-Zhong Zhang Rick Tourdot [Video]	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
Dec 6	Vicky Yao [Video]	Troyanskaya Lab, Lewis-Sigler Institute for Integrative Genomics, Princeton University	Primer: Integrated, tissue-specific analysis of biological data

Fall 2017
Date	Speaker	Affiliations	Title
Dec 6	Olga Troyanskaya	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
Nov 29	Joseph Nasser	Lander Lab, Broad Institute	Primer: Introduction to Hi-C
Nov 29	Erez Lieberman Aiden	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
Nov 15	Jennifer Listgarten [Video]	Microsoft Research	Machine-learning-based CRISPR guide design
Nov 8	Nicolo Fusi [Video]	Microsoft Research	Automated Machine Learning
Nov 1	Alex Wein [Video]	Dept. of Mathematics, Massachusetts Institute of Technology	Message passing algorithms for cryo-EM and synchronization
Oct 25	David Reshef Yakir Reshef [Video]	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
Oct 25	David Reshef Yakir Reshef [Video]	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
Oct 11	Michael Rooney [Video]	Neon Therapeutics	Primer: Intro to tumor immunity
Oct 11	Sisi Sarkizova Michael Rooney [Video]	Hacohen Lab, Broad Institute, Massachusetts General Hospital Neon Therapeutics	Improving endogenous antigen prediction to support personalized cancer vaccine development
Oct 4	Hilary Finucane [Video]	Medical and Population Genetics, Broad Institute	Insight into the biology of common diseases using summary statistics of large genome-wide association studies
Sep 27	[Video]		Primer: A tutorial on optimal transport
Sep 27	Geoffrey Schiebinger [Video]	Broad Institute; Statistics and Data Science Center, Massachusetts Institute of Technology	Learning developmental landscapes from single-cell gene expression with optimal transport
Sep 20	Nick Patterson [Video]	Broad Institute; Reich Lab, Harvard University	Learning phylogeny through f-statistics
Sep 13	Ran Cui [Video]	Finucane Lab, Broad Institute	Primer: Generalized least squares
Sep 13	Yakir Reshef [Video]	Dept. of Computer Science, Harvard University; Harvard/MIT MD-PhD Program, Harvard Medical School	Detecting effects of transcription factors on disease
Sep 6	David Kelley [Video]	Calico Life Sciences	Reading the rules of gene regulation from the human noncoding genome
Sep 6	Samuel Friedman [Video]	Data Sciences Platform, Broad Institute	Classifying genomic sequences with convolutional neural networks

Fall 2016
Date	Speaker	Affiliations	Title
Dec 14	Daniel King [Video]	Hail Team, Neale Lab, Broad Institute	What is a compiler?
Dec 14	Daniel Huang [Video]	The Programming Languages Group, Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS)	Compiling probabilistic programs

Fall 2016
Date	Speaker	Affiliations	Title
Dec 7	Karsten Krug [Video]	Proteomics Platform, Broad Institute	Mass spectrometry-based proteomics
Dec 7	Ryan Peckner [Video]	Proteomics Platform, Broad Institute	Spectral unmixing for next-generation mass spectrometry proteomics
Nov 16	Babak Ehteshami Bejnordi [Video]	Beck Lab, Harvard Medical School	Practical recommendations for training convolutional neural nets
Nov 16	Dayong Wang Andy Beck [Video]	Beck Lab, Harvard Medical School Dept. of Pathology, Harvard Medical School	Deep learning for computational pathology
Nov 9	David Benjamin [Video]	Data Sciences Platform, Broad Institute	Dirichlet processes
Nov 9	Quaid Morris [Video]	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
Nov 2	Anshul Kundaje [Video]	Depts. of Genetics and Computer Science, Stanford University	Integrative, interpretable deep learning frameworks for regulatory genomics and epigenomics
Oct 26	Alex Wiltschko [Video]	Twitter Cortex	Automatic differentiation, the algorithm behind all deep neural networks
Oct 26	Umut Eser [Video]	Churchman Lab, Harvard Medical School	FIDDLE: An integrative deep learning framework for functional genomic data inference
Oct 12	Ann Sizemore [Video]	Cancer Program, Broad Institute	Topological data analysis: What is persistent homology?
Oct 12	Chad Giusti [Video]	Dept. of Mathematics, Warren Center for Network and Data Sciences, University of Pennsylvania	Topological data analysis: What can persistent homology see?
Sep 28	Adrian Veres [Video]	Dept. of Systems Biology, Harvard University; Harvard-MIT Health Sciences and Technology	Experimental and computational techniques underlying RNA-seq
Sep 28	Rafael Irizarry [Video]	Dept. of Data Sciences, Dana-Farber Cancer Institute; Dept. of Biostatistics, Harvard School Public Health	Overcoming bias and batch effects in high-throughput data
Sep 21	Rajesh Ranganath [Video]	Dept. of Computer Science, Princeton University	Probabilistic generative models and posterior inference
Sep 21	Alp Kucukelbir [Video]	Dept. of Computer Science, Columbia University	Automated inference and the promise of probabilistic programming
Sep 14	Brian Cleary [Video]	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
Sep 14	Alex Bloemendal	Hail Team, Neale Lab, Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital	Introduction to compressed sensing

Spring 2016
Date	Speaker	Affiliations	Title
Jun 1	Su-In Lee	Depts. of Genome Sciences, Electrical Engineering, and Computer Science, University of Washington	Identifying molecular markers for cancer treatment from big data
May 25			MIA Breakfast Social
May 18	Tim Poterba Jon Bloom [Video]	Hail Team, Neale Lab, Broad Institute Hail Team, Neale Lab, Broad Institute	Basic introduction to distributed computation

Spring 2016
Date	Speaker	Affiliations	Title
May 18	Matei Zaharia [Video]	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
May 11	David Benjamin [Video]	Data Sciences Platform, Broad Institute	Variational Bayesian inference
May 11	David Blei [Video]	Depts. of Statistics and Computer Science, Data Science Institute, Columbia University	Scaling and generalizing variational inference
May 4	Yakir Reshef [Video]	Harvard Intelligent Probabilistic Systems, Harvard University; Harvard Medical School; Massachusetts Institute of Technology	Gaussian processes
May 4	Barbara Engelhardt [Video]	Dept. of Computer Science, Princeton University	Bayesian structured sparsity: Rethinking sparse regression
Apr 27	Ryan Peckner [Video]	Genetic Perturbation Platform, Broad Institute	Linear codes
Apr 27	Yaniv Erlich [Video]	Dept. of Computer Science, Columbia University; NY Genome Center	Compressed experiments
Apr 27	David Tse [Video]	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
Apr 20	Manuel Rivas	Daly Lab, Massachusetts General Hospital; Broad Institute	Multiple testing and false discovery rate
Apr 20	Joshua Weinstein	Zhang Lab, Broad Institute	DNA microscopy and the sequence-to-image inverse problem
Apr 13	Joseph Nasser	Connectivity Map, Broad Institute	t-dist. stochastic neighbor embedding (t-SNE)
Apr 13	Shantanu Singh Anne Carpenter Mohammad Rohban	Carpenter Lab, Broad Institute Imaging Platform, Broad Institute Carpenter Lab, Broad Institute	Information in cell images: Targeting diseases and characterizing compounds
Apr 6	David Kelley	Rinn Lab, Dept. of Stem Cell and Regenerative Biology, Harvard University	Convolutional neural nets
Apr 6	Abraham Heifets	Atomwise	AtomNet: a deep convolutional neural net for bioactivity prediction in structure-based drug discovery
Mar 30	David Rolnick	Dept. of Mathematics, Massachusetts Institute of Technology	Non-negative matrix factorization (NMF)
Mar 30	John Wakeley	Dept. of Organismic and Evolutionary Biology, Harvard University	The effects of population pedigrees on gene genealogies
Mar 23	Alex Bloemendal	Hail Team, Neale Lab, Broad Institute	Linear models III: regularization, LASSO and sparsity
Mar 23	D. Sculley	Google Brain, Google Research Cambridge	A quick introduction to TensorFlow and related API's
Mar 16	Yakir Reshef	Harvard Intelligent Probabilistic Systems, Harvard University; Harvard Medical School; Massachusetts Institute of Technology	Linear models II: Regularization and ridge
Mar 16	Jeremy Freeman [Video]	Janelia Research Campus; Howard Hughes Medical Institute	Open source tools for large-scale neuroscience

Spring 2016
Date	Speaker	Affiliations	Title
Mar 9	Hilary Finucane	Price Lab, Harvard School of Public Health; Dept. of Mathematics, Massachusetts Institute of Technology	Linear models I: Ordinary least squares
Mar 9	Po-Ru Loh	Price Lab, Harvard School of Public Health	Haplotype phasing in large cohorts: Modeling, search, or both?
Mar 2	Giulio Genovese	McCarrol Lab, Broad Institute; Dept. of Genetics, Harvard Medical School	Hidden Markov models II
Mar 2	Leonid Mirny	Dept. of Physics, Institute for Medical Engineering and Science, Massachusetts Institute of Technology	Polymer models of chromosomes
Feb 24	Giulio Genovese	McCarrol Lab, Broad Institute; Dept. of Genetics, Harvard Medical School	Hidden Markov models I
Feb 24	Geoffrey Schiebinger	Dept. of Statistics, UC Berkeley	Sparse inverse problems
Feb 17	Jon Bloom	Hail Team, Neale Lab, Broad Institute; Dept. of Mathematics, Massachusetts Institute of Technology	Frequentist vs Bayesian inference
Feb 17	Caroline Uhler [Video]	Dept. of Electrical Engineering and Computer Science, Institute for Data, Systems and Society (IDSS), Massachusetts Institute of Technology	Gene regulation in space and time
Feb 10	David Benjamin	Data Sciences Platform, Broad Institute	Primer: Principal component analysis (PCA)
Feb 10	Jeremy Gunawardena	Dept. of Systems Biology, Harvard University	Systems biology: Can mathematics lead experiments?
Feb 3	Shamil Sunyaev	Dept. of Biomedical Informatics, Harvard University; Brigham and Women's Hospital; Broad Institute	Judging the importance of human mutations using evolutionary models
Jan 27	Brendan Frey	Depts. of Electrical and Computer Engineering, Computer Science, and Medical Research, University of Toronto; Deep Genomics	Genomic medicine: Will software eat bio?

Fall 2015
Date	Speaker	Affiliations	Title
Nov 30	Matthew Johnson	Datta Lab, Harvard Intelligent Probabilistic Systems, Harvard University	TS II. Modeling structure in time series
Nov 23	Alex Wiltschko	Datta Lab, Harvard Intelligent Probabilistic Systems, Harvard University; Twitter	TS I. Mapping sub-second structure in mouse behavior
Nov 16	David Kelley	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
Nov 12	Ryan Adams [Video]	The Original HIPSter, Twitter Cortex, Talking Machines	Machine learning and the life sciences: Beyond data analysis
Nov 9	David Duvenaud	Harvard Intelligent Probabilistic Systems, Harvard University	NN II. Convolutional networks on graphs for learning molecular fingerprints
Nov 2	Dougal Maclaurin	Harvard Intelligent Probabilistic Systems, Harvard University	NN I. Reverse-mode differentiation and autograd
Oct 19	Scott Linderman	Harvard Intelligent Probabilistic Systems, Harvard University	DM II. Discrete models with continuous latent structure: A new hope
Oct 13	Jon Bloom	Broad Institute	DM I. Bayesian logistic regression and mixed models: Revenge of the Gibbs

Fall 2015
Date	Speaker	Affiliations	Title
Sep 21	Alex Bloemendal	Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital	CS2: Compressed sensing
Sep 21	Brendan Meade	Dept. of Earth and Planetary Sciences, Harvard University; Google Research	CS1: Exploiting sparse and quantized signals to solve linear systems
Sep 14	Nikolai Slavov	Dept. of Bioengineering, Northeastern University	Quantifying protein isoforms

Summer 2015
Date	Speaker	Affiliations	Title
Jul 27	Andrea Byrnes	Broad Institute; Harvard Medical School; Massachusetts General Hospital	Challenges in normalization of RNAseq data
Jul 20	Brendan Bulik-Sullivan	Broad Institute	LD score regression for distinguishing confounding from polygenicity
Jul 13	Mark Flaherty	Data Sciences Platform, Broad Institute	Introduction to evolutionary algorithms and NEAT
Jul 6	David Benjamin	Data Sciences Platform, Broad Institute	The Chinese restaurant process and Indian buffet process
Jun 29	David Benjamin	Data Sciences Platform, Broad Institute	Introduction to Dirichlet processes
Jun 22	Bertrand Haas	Broad Institute	Conjugate priors and Hardy-Weinberg equilibrium (Bishop, Ch2)
Jun 15	Jon Bloom	Broad Institute	Discussion of Pachter's p-value prize
Jun 8	Bertrand Haas	Broad Institute	Choosing priors in Bayesian inference
Jun 1	Heng Li	Broad Institute	Graph-based genetic sequence representation

Spring 2015
Date	Speaker	Affiliations	Title
May 4	Jon Bloom	Broad Institute	Introduction to Gaussian processes and Bayesian optimization (Bishop, Ch6)
Apr 28	Ian Smith	Broad Institute	Connectivity map and challenges in data normalization
Apr 14	Brendan Bulik-Sullivan	Broad Institute	Linear mixed models for genetic association analysis
Apr 7	Yossi Farjoun	Data Sciences Platform, Broad Institute	Genetic fingerprints and contamination estimation
Mar 30	Alex Bloemendal	Dept. of Mathematics, Harvard University	Markov Chain Monte Carlo and Gibbs sampling on Gaussian mixture models (Bishop, Ch11)
Mar 23	Laura Gauthier Bertrand Haas	MacArthur Lab, Data Sciences Platform, Broad Institute Broad Institute	Variant quality score recalibration
Mar 16	Cotton Seed	Dept. of Mathematics, Massachusetts Institute of Technology	Variational Bayes and inference on Gaussian mixture models (Bishop, Ch10)
Mar 9	Jon Bloom	Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute	Expectation maximization and inference on Gaussian mixture models (Bishop, Ch9)

Spring 2015
Date	Speaker	Affiliations	Title
Mar 2	Jon Bloom	Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute	Introduction to Bayesian graphical models: the Gaussian mixture model (Bishop, Ch8)
Feb 24	Alex Bloemendal Jon Bloom Bertrand Haas Cotton Seed	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
Jan 26	Bertrand Haas	Broad Institute	Independent component analysis (ICA) and projection pursuit

Fall 2014
Date	Speaker	Affiliations	Title
Dec 15	Jon Bloom Cotton Seed	Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute Dept. of Mathematics, Massachusetts Institute of Technology	Non-linear dimensional reduction: tSNE and diffusion maps
Dec 8	Alex Bloemendal	Dept. of Mathematics, Harvard University	Non-negative matrix factorization (NMF)
Nov 24	Alex Bloemendal	Dept. of Mathematics, Harvard University	Principle component analysis (PCA) and the Marchenko-Pastur law
Nov 3	Jon Bloom Bertrand Haas	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
Oct 27	Jon Bloom	Dept. of Mathematics, Massachusetts Institute of Technology; Broad Institute	Optimal coverage in rare variant association studies
Oct 20	Yossi Farjoun	Broad Institute	Detecting sample swap
Oct 6	Bertrand Haas	Broad Institute	Contingency tables III: Examples in genetics
Sep 29	Bertrand Haas	Broad Institute	Contingency tables II: Correlation, Pearson chi-squared test, and Fisher exact test
Sep 22	Bertrand Haas	Broad Institute	Contingency tables I: t-test and z-test

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