The mission of the Flatiron Institute is to advance scientific research through computational methods, including data analysis, theory, modeling and simulation.

Simons Foundation

Featured News

An illustration of a person looking at a vase of flowers and a cup of tea.

Global Brain Mapping Mouse Brains Points to How Autism Can Affect Expectation Updating By Jane Beaufore

A new study finds that mice with variants in autism-associated genes have difficulty flexibly updating their expectations. The mice relied more on frontal brain areas associated with cognition and reasoning rather than sensory-processing brain regions to process prior information about the world. The results provide new insights into the neurobiology of autism.

Illustration of researchers working at a computer surrounded by helpful modules and agents, depicted as floating cubes

Flatiron Institute Meet Denario — An AI Assistant for Every Step of the Scientific Process

An illustration of a star's cross-section with an overlay of MESA code and charts.

Center for Computational Astrophysics A Stellar Revolution: How Open-Source Tool MESA Changed the Way We Study Stars

Our Centers

Center for Computational Astrophysics

Center for Computational Biology

Center for Computational Mathematics

Center for Computational Neuroscience

Center for Computational Quantum Physics

Scientific Computing Core

It develops, deploys and maintains computational infrastructure — from supercomputers to desktop PCs — dedicated solely to the use of Flatiron researchers.

Initiatives

Initiative for Computational Catalysis

The Simons Foundation Initiative for Computational Catalysis is a new effort within the Flatiron Institute dedicated to the development and application of computational techniques enabling the rational design of more efficient and more affordable catalysts.

Foundation Models of Science

Our goal is to accelerate the development of versatile foundation models tailored for numerical datasets and scientific machine learning tasks. The challenge we are undertaking is to build AI models which leverage information from heterogeneous datasets and across different scientific fields, which, contrary to domains like natural language processing, do not share a unifying representation.

Collaborative Work

Machine Learning at the Flatiron Institute

Machine learning has become an indispensable tool for computational science, and it is an active and growing area of research throughout the Flatiron Institute.

Structural and Molecular Biophysics

Underlying all biological processes are molecules and their interactions with each other. However, our ability to understand how these molecules function over biologically relevant scales remains very limited.

Learning the Universe

This collaboration aims to understand and determine the evolution and initial conditions of our universe, using observations via a Bayesian forward modeling approach.

CCA
| Columbia University
| Lawrence Berkeley National Lab
| Harvard University
| Stockholm University
| Institute D'Astrophysique de Paris
| Université de Montreal
| Princeton University
| Carnegie Mellon University
| Max-Planck Institute for Astrophysics

Flatiron Institute Idea Scholar Program

For distinguished scientists interested in developing scientific talent in the workforce and enabling pathways to science

Scholars may engage in a variety of activities, such as working on scientific projects, starting new collaborations, mentoring junior scientists, and organizing or participating in workshops and career development events.

Learn More

A major effort of the Flatiron Institute is the development and support of high-quality, open-source software for research.

View All Software

Research Highlights

October 30, 2025

Neurons as Detectors of Coherent Sets in Sensory Dynamics

J. Pughe-Sanford, X. Ding, J. Moore, A. Sengupta, C. Epstein, P. Greengard, D. Chklovskii

We model sensory streams as observations from high-dimensional stochastic dynamical systems and conceptualize sensory neurons as self-supervised learners of compact…

arXiv:2510.26955

October 23, 2025

Scalable inference of functional neural connectivity at submillisecond timescales

A. Medvedeva, E. Balzani, A. Williams, Stephen L Keeley

The Poisson Generalized Linear Model (GLM) is a foundational tool for analyzing neural spike train data. However, standard implementations rely…

arXiv:2510.20966

October 2, 2025

Learning a distance measure from the information-estimation geometry of data

G. Ohayon, P. Fiquet, F. Guth, Jona Ballé, E. P. Simoncelli

We introduce the Information-Estimation Metric (IEM), a novel form of distance function derived from an underlying continuous probability density over…

rXiv:2510.02514

News & Announcements

Center for Computational Astrophysics

December 03, 2025

Groundbreaking Simulations Show How Black Holes Glow Bright By Thomas Sumner

Still from a simulation showing a cross section of an accretion disk around a black hole.

Center for Computational Biology

November 17, 2025

From Ring to Keyhole: Modeling How Tissues Mold the Fruit Fly’s Gut By Jane Beaufore

Flatiron Institute

November 15, 2025

CCN’s SueYeon Chung Named a ‘Rising Star in Neuroscience’ By Jane Beaufore

Leadership

Leslie Greengard, M.D., Ph.D.

Director, CCM

Leslie Greengard joined the Simons Foundation in 2013 as founding director of the Simons Center for Data Analysis, now called the Center for Computational Biology. Prior to that, Greengard served as director of the Courant Institute of Mathematical Sciences at New York University.

Julianne Dalcanton, Ph.D.

Director, CCA

Julianne Dalcanton joined the Simons Foundation in September 2021 as the director of the Flatiron Institute’s Center for Computational Astrophysics (CCA). Her research specializes in the origins and evolution of galaxies.

Ian Fisk, Ph.D.

Chief Technology Officer, Simons Foundation

Ian Fisk came to the Simons Foundation in 2014 after working in the computing division at the Fermi National Accelerator Laboratory in Illinois since 2003. Fisk was the Compact Muon Solenoid (CMS) experiment’s computing coordinator at CERN from 2010 to 2013, overseeing operations and improvements…

Antoine Georges, Ph.D.

Director, CCQ

Antoine Georges is a professor of physics at the Collège de France, where he holds the chair in condensed matter physics. He also has joint appointments with École Polytechnique and the University of Geneva. He received his Ph.D. from the École Normale Supérieure in 1988.…

Andrew Millis, Ph.D.

Co-Director, CCQ

Andrew Millis is co-director of the Center for Computational Quantum Physics at the Flatiron Institute and professor of physics at Columbia University. He currently serves as Managing Director of the Flatiron Institute.

Michael Shelley, Ph.D.

Director, CCB

Michael Shelley joined the Simons Foundation in 2016 to work on the modeling and simulation of complex systems arising in physics and biology.

Eero P. Simoncelli, Ph.D.

Director, CCN

Eero P. Simoncelli is the inaugural director of the Center for Computational Neuroscience. Eero P. Simoncelli’s research interests span a wide range of topics in the representation and analysis of visual images and sounds in both machine and biological vision systems.