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: Juliana Freire

Chair of Steering Committee: Mik Laver

Principal Investigator: Juliana Freire

Steering Committee

Richard Bonneau, Computer Science and Biology
Kyle Cranmer, Physics (Chair: Reproducibility and Open Science Working Group)
Juliana Freire, Computer Science & Engineering (Chair: Reproducibility and Open Science Working Group)
David Hogg, Physics (Chair: Space Working Group)
Mik Laver, Politics (Chair: Careers Working Group)
Yann LeCun, Computer Science
Laura Norén, MSDSE (Chair: Data Science Studies Working Group)
Dennis Shasha, Computer Science
Claudio Silva, Computer Science & Engineering (Chair: Software and Tools Working Group)
Eero Simoncelli, Center for Neural Science
Carlos Fernandez-Granda, Mathematics and Data Science (Chair: Methods Working Group)
Arthur Spirling, Politics and Data Science (Chair: 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
Jonathan Nagler, Politics
Patrick Perry, Information, Operations and Management Sciences
Daniele Panozzo, Computer Science
Joshua Tucker, Politics
Daniele Panozzo, Computer Science

Research Engineers

Harish Doraiswamy
Stefan Karpinski
Heiko Müller
Remi Rampin

Data Science Fellows

Alexander Bock
Djellel Difallah
Michael Z. Gill
Bruno Gonçalves
Daniela Huppenkothen
Gilles Louppe
Brian McFee
Tassos Noulas
Soledad Villar

Post-Docs

Neil Bramley
Johann Brehmer
Andreu Casas
Richard Galvez
Krzysztof Geras
Thomas Laetsch
Laura Norén

PhD Students

Fernando Seabra Chirigati

Junior Data Scientists

Manoj Kumar Sivaraj
Seongwoo Han
Zhongheng Li
Shaivi Kochar
Prashantkumar Patel

Outreach

Vicky Steeves (NYU Libraries)

Program Manager

Emily Mathis

Visitors/Alumni

Dan Cervone
Jean-Daniel Fekete
Zaid Harchaoui
Taisiya Kopytova
Pablo Barberá
Andreas Mueller
Ling Yang
Foster Provost
Roy Lowrance
Daniel Fernandez
Vighnesh Nandan Birodkar
Jiaming Dong
Katrina Evtimova
Shwet Maroo
Jiyuan Qian
Tian Wang
Andrea Jones-Rooy
Sunandan Chakraborty
Andrew Guess