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.
Since the inception of the Moore-Sloan initiative, the project has been spearheaded by the leadership of the several individuals, whose invaluable contributions have inspired programmatic momentum, growth, and vision. As the inaugural Executive Director and PI of the Moore-Sloan project in 2013, Yann LeCun (Professor of Computer Science) was instrumental in shaping MSDSE’s mission by recruiting its first class of research fellows, engineers, and postdoctoral associates, and laying the foundational groundwork for the Center for Data Science as its first Director. Yann’s tenure was followed by that of David Hogg (Professor of Physics). “This initiative isn’t just to ‘do’ science—it is to ‘change’ science,” said Hogg of his work with Moore-Sloan. “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.”
In 2015 the Moore-Sloan torch was passed to Juliana Freire (Professor of Computer Science and Engineering), who built on the legacy of LeCun and Hogg by engaging the university community more broadly in Moore-Sloan efforts through the seed grant program, summer research internships, and postdoctoral associate competition. As the first woman honored to be elected as Chair of ACM SIGMOD, and an appointee to the National Academies of Sciences, Engineering, and Medicine committee on Reproducibility and Replicability in Science, Freire brought her breadth of distinguished experience and knowledge to the grant. Under Freire’s direction Moore-Sloan activities grew as activities such as the lunch seminars, showcases, and Text as Data seminar series attracted an increasing number of participants not just across diverse fields and departments, but across the broader New York City data science community. Finally, Freire’s leadership saw the growth of the Moore-Sloan Fellow program, as the inaugural class of fellows graduated with a 100% placement record to prestigious positions across academia and industry, and applicants to the new fellow positions swelled in ever-increasing number and elite qualifications, proving the expansive influence and reach of the Moore-Sloan brand. In late 2018 MSDSE leadership transitioned to Kyle Cranmer (Professor of Physics and Data Science), who is focused on sustaining the most successful parts of MSDSE into the future: MSDSE is launching a Data Science & Software Services (DS3) initiative to better utilize the university’s data science capacity and expand opportunities for engagement to every corner of the university and beyond.
CDS Data Science newsletter sign-up.
Executive Director: Kyle Cranmer
Chair of Steering Committee: Arthur Spirling
Principal Investigator: Kyle Cranmer
- Richard Bonneau, Computer Science and Biology
- Kyle Cranmer, Physics (MSDSE Executive Director and PI, Chair of the Reproducibility and Open Science Working Group)
- Juliana Freire, Computer Science & Engineering (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 (Steering Committee Chair, Chair of the Education and Training Working Group)
- Julia Kempe, CDS (Director of Center for Data Science)
Data Science Fellows
- Vicky Steeves (NYU Libraries)