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

A visualization shows a giant flare erupting from a magnetized star called a magnetar.

Center for Computational Astrophysics Flares From Magnetized Stars Can Forge Planets’ Worth of Gold, Other Heavy Elements Mara Johnson-Groh

Flatiron Institute researchers have identified a previously unknown way to make the universe’s heaviest atoms, such as gold, platinum and uranium. They calculate that a single flare from a supermagnetized star called a magnetar can produce the mass equivalent of 27 moons’ worth of these elements in one go.

Stylized image of bacteria swimming though an obstacle-filled liquid

Center for Computational Biology New Model Predicts How Bacteria Navigate Obstacles to Spread

Flatiron Institute New Datasets Will Train AI Models to Think Like Scientists

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, directed by Greg Bryan of Columbia University, 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.

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Research Highlights

2025

Superfast Direct Inversion of the Nonuniform Discrete Fourier Transform via Hierarchically Semiseparable Least Squares

Heather Wilber, Ethan N. Epperly, A. Barnett

A direct solver is introduced for solving overdetermined linear systems involving nonuniform discrete Fourier transform matrices. Such matrices can be…

SIAM Journal on Scientific Computing

2025

Sampling From Multiscale Densities With Delayed Rejection Generalized Hamiltonian Monte Carlo

G. Turok, C. Modi, B. Carpenter

Hamiltonian Monte Carlo (HMC) is the mainstay of applied Bayesian inference for differentiable models. However, HMC still struggles to sample…

Proceedings of The 28th International Conference on Artificial Intelligence and Statistics

2025

Level Set Teleportation: An Optimization Perspective

Aaron Mishkin, A. Bietti, R. M. Gower

We study level set teleportation, an optimization routine which tries to accelerate gradient descent (GD) by maximizing the gradient norm…

The 28th International Conference on Artificial Intelligence and Statistic

News & Announcements

Simons Foundation

May 07, 2025

10 Simons Foundation Community Members Elected to National Academy of Sciences By Jane Beaufore

Center for Computational Astrophysics

April 30, 2025

A Vast Molecular Cloud, Long Invisible, Is Discovered Near Our Solar System

Center for Computational Astrophysics

April 29, 2025

Flares From Magnetized Stars Can Forge Planets’ Worth of Gold, Other Heavy Elements Mara Johnson-Groh

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.