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

Illustration of an optical lattice, which looks like an egg crate, with pairs of particles sitting in various pockets of the lattice.

Center for Computational Quantum Physics Scientists Capture Superconductivity’s ‘Dancing Pairs’ for First Time, Filling Gap in Decades-Old Theory By Mara Johnson-Groh

Analysis of a first-of-its-kind experiment reveals missing pieces in the decades-old theory of superconductivity.

A 3D rendering of components inside a cell that make up the human mitotic spindle.

Center for Computational Biology The Machinery That Helps Divide Your Cells Self-Organizes Like an Active Liquid Crystal

Illustration of the dust shell traveling away from a black hole and gas being pulled back towards it.

Center for Computational Astrophysics Caught in the Act: Astronomers Watch a Vanishing Star Turn Into a Black Hole

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

April 10, 2026

Estimating Dimensionality of Neural Representations from Finite Samples

C. Chun, A. Canatar, S. Chung , Daniel Lee

The global dimensionality of a neural representation manifold provides rich insight into the computational process underlying both artificial and biological…

International Conference on Learning Representations (ICLR)

April 10, 2026

Partial Soft-Matching Distance for Neural Representational Comparison with Partial Unit Correspondence

Chaitanya Kapoor, A. Williams, Meenakshi Khosla

Representational similarity metrics typically force all units to be matched, making them susceptible to noise and outliers common in neural…

International Conference on Learning Representations (ICLR)

April 10, 2026

Quasi Monte Carlo methods enable extremely low-dimensional deep generative models

Miles Martinez, A. Williams

This paper introduces quasi-Monte Carlo latent variable models (QLVMs): a class of deep generative models that are specialized for finding…

International Conference on Learning Representations (ICLR)

News & Announcements

Center for Computational Neuroscience

April 29, 2026

CCN Director Eero Simoncelli Elected to National Academy of Sciences

Flatiron Institute

April 28, 2026

Pilar Cossio: Reconstructing RNA’s Shapeshifting Behavior By Marcus Banks

A photo of Pilar Cossio sitting in front of a shelf of math books.

Center for Computational Mathematics

April 23, 2026

American Academy of Arts and Sciences Elects CCM’s Charles Epstein

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.