Past Events

The Eric and Wendy Schmidt Center hosts workshops, colloquia, and challenges that bring together global experts, machine learning and biology enthusiasts, students, postdocs, and researchers to define and collaborate on the biggest challenges at the nexus of machine learning and biology.
Dana Pe'er
November 6, 2023

Sloan Kettering Institute

Trey Ideker
October 2, 2023

Trey Ideker (UC San Diego) gave a talk on "Building a mind for cancer."

Marinka Zitnik
September 7, 2023

Marinka Zitnik (Harvard Medical School) gave a colloquium entitled "Foundation models for therapeutic design and treatment prediction."

Fabian Theis
July 6, 2023

Fabian Theis (Helmholtz Munich) gave a colloquium entitled "Generative AI for modeling single-cell responses."

Mikhail Belkin
May 8, 2023

Mikhail Belkin (UC San Diego) gave a talk entitled "The challenges of training infinitely large neural networks."

Anna Goldenberg
April 10, 2023

Anna Goldenberg (SickKids Research Institute and University of Toronto) gave a colloquium entitled "Time series ML for deployment in healthcare."

Jennifer Listgarten
March 31, 2023

Jennifer Listgarten (UC Berkeley) gave a colloquium entitled "Some thoughts on machine-learning based protein engineering."

David Baker
March 6, 2023

David Baker (University of Washington) gave a colloquium on "Protein design using deep learning."

Ziad Obermeyer
February 23, 2023

Ziad Obermeyer (UC Berkeley) gave a colloquium entitled "Machine earning about sudden cardiac death from ECG waveforms."

Jure Leskovec
February 6, 2023

Jure Leskovec (Stanford University) gave a colloquium entitled "Towards universal cell embeddings."

Cancer Immunotherapy Data Science Grand Challenge
January 9, 2023

While T cells, our immune system's fighter cells, should, in theory, recognize and kill growing tumors, cancer cells send signals to T cells that cause these fighter cells to malfunction. But what if we could modify individual genes in T cells to stop this process — and transform T cells into more effective tumor destroyers? To that end, the Eric and Wendy Schmidt Center and collaborators are calling on machine learning enthusiasts to identify genetic modifications to make T cells better at killing cancer cells. Top submissions will be tested out in a lab at the Broad.

Smita Krishnaswamy
November 3, 2022

Smita Krishnaswamy (Yale University) gave a colloquium entitled "Multiscale diffusion-based flows and embeddings for molecular and cellular data."

Michael Bronstein
October 20, 2022

Michael Bronstein (University of Oxford) gave a colloquium on “Geometric deep Learning and applications to proteins.”

Jay Bradner
May 26, 2022

Jay Bradner (president of the Novartis Institute for Medical Research) gave a talk on “The new science of therapeutics.”

The Convergence of AI and Biology: Insights into the Biology of Tissues
April 7, 2022

The workshop brought together experts in biology, computation, and technology development for talks and discussions centered on tissue modelling, cell communication, and machine learning.

Co-hosted with the Klarman Cell Observatory

Yoshua Bengio
February 8, 2022

Yoshua Bengio (founder and scientific director of the Mila - Quebec AI institute) spoke at EWSC's February colloquium.

The Convergence of AI and Biology: Advancing Our Understanding of the Cell
December 9, 2021

This workshop featured speakers from multiple disciplines that are taking on some of the toughest challenges at the interface of cellular biology, computational method development — and advances in the technology to power both.

Co-hosted with the Gene Regulation Observatory

G.V. Shivashankar
November 29, 2021

G.V. Shivashankar (head of the Laboratory of Nanoscale Biology, Paul Scherrer Institute and Professor of Mechano-Genomics, ETH Zurich) shared insights on understanding the role that mechano-chemical signals play in regulating cell-state transitions.

Bradley Bernstein
October 19, 2021

Bradley Bernstein (director of the Gene Regulation Observatory at the Broad Institute and chair of the Cancer Biology at the Dana-Farber Cancer Institute) researches how changes to the protein scaffold of genes contribute to development and cancer.

Perturbations, Therapeutics, and Machine Learning Workshop
September 28, 2021

Speakers from multiple disciplines shared their insights into taking on some of the toughest challenges at the interface of machine learning and biology.

Co-hosted with the Jameel Clinic

Rick Young
September 14, 2021

Rick Young (professor of Biology at MIT and core member of the Whitehead Institute) researches gene expression differences in healthy and diseased cells.

Opportunities at the Interface of Machine Learning and Medicine
June 3, 2021

A discussion and plenary sessions on the biggest questions driving machine learning in clinical medicine and biology.