Moore-Sloan Data Science Environment – Overview

New York University, the University of California, Berkeley and the University of Washington have launched a 5-year, $37.8 million, cross-institutional effort with support from the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation to harness the potential of data scientists and big data for basic research and scientific discovery. NYU competed nationally with fifteen leading universities in the field of data science for this prestigious award, and will receive $12.6 million for its data science enterprise through this initiative.

This bold new partnership—a coordinated, distributed experiment involving researchers at these three leading universities—hopes to establish models that will dramatically accelerate the data science revolution. While data science is already contributing to scientific discovery, substantial systemic changes need to be overcome to maximize its impact on academic research. This ambitious multi-institutional partnership will spur collaborations within and across the three campuses and other partners pursuing similar data-intensive science goals.

“This initiative isn’t just to ‘do’ science—it is to ‘change’ science. To that end, we have designed a set of programs and positions at NYU that will help scientists in the domains—for example, astronomy, psychology, and sociology—interact with scientists in the methods—applied mathematics, statistics, and computer science—to make both groups of scientists more capable and more successful.” – Prof. David Hogg, Moore-Sloan Data Science Environment.

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Executive Director: Kyle Cranmer

Chair of Steering Committee: TBD

Principal Investigator: Kyle Cranmer

Steering Committee

Richard Bonneau, Computer Science and Biology
Kyle Cranmer, Physics (PI and Executive Director of the MSDSE, Co-Chair of the Reproducibility and Open Science Working Group)
Juliana Freire, Computer Science & Engineering (Executive Director of the MSDSE, Co-Chair of the Reproducibility and Open Science Working Group)
David Hogg, Physics (Chair of the Space Working Group)
Yann LeCun, Computer Science
Dennis Shasha, Computer Science
Claudio Silva, Computer Science & Engineering (Chair of the Software and Tools Working Group)
Eero Simoncelli, Center for Neural Science
Carlos Fernandez-Granda, Mathematics and Data Science (Chair of the Methods Working Group)
Arthur Spirling, Politics and Data Science (Chair of the Education and Training Working Group)

Affiliated Faculty

Meredith Broussard, Journalism
Kyunghyun Cho, CDS
Scott Collard, NYU Libraries
Jennifer Hill, Applied Statistics and Data Science
Brenden Lake, CDS
Brian McFee, CDS
Jonathan Nagler,Politics
Patrick Perry, Information, Operations and Management Sciences
Daniele Panozzo, Computer Science
Krzysztof Geras, School of Medicine
Joshua Tucker, Politics

Research Engineers

Harish Doraiswamy
Stefan Karpinski
Heiko Müller
Remi Rampin

Data Science Fellows

Alexander Bock
Djellel Difallah
Michael Z. Gill
Tassos Noulas
Soledad Villar


Neil Bramley
Johann Brehmer
Andreu Casas
Richard Galvez
Katharina Kann
Thomas Laetsch

PhD Students

Fernando Seabra Chirigati
Vladimir Kobzar

Junior Data Scientists

Tianyi Bi


Vicky Steeves (NYU Libraries)

Program Manager

Emily Mathis


Dan Cervone
Jean-Daniel Fekete
Zaid Harchaoui
Taisiya Kopytova
Pablo Barberá
Andreas Mueller
Manoj Kumar Sivaraj
Seongwoo Han
Zhongheng Li
Shaivi Kochar
Prashantkumar Patel
Ling Yang
Foster Provost
Roy Lowrance
Daniel Fernandez
Vighnesh Nandan Birodkar
Jiaming Dong
Katrina Evtimova
Shwet Maroo
Jiyuan Qian
Tian Wang
Andrea Jones-Rooy
Gilles Louppe
Sunandan Chakraborty
Andrew Guess
Mik Laver
Laura Norén
Bruno Gonçalves
Xintian Han
Khushnaseeb Ali
Preet Gandhi
Chaitra Hegde
Binal Jayeshkumar Modi