Harvard Data Science Initiative Awarded Grant from the Alfred P. Sloan Foundation

July 29, 2020

The Harvard Data Science Initiative (HDSI) has received a generous grant from the Alfred P. Sloan Foundation to support a team of Harvard faculty working on new methods for causal inference and machine learning.

“Existing causal inference methods largely address simple situations where the intervention is binary—for example, receiving treatment or not—and the observations are independent across time and space,” explains Francesca Dominici, Clarence James Gamble Professor of Biostatistics, Population, and Data Science at the Harvard T.H. Chan School of Public Health, HDSI Faculty Co-Director, and the project’s Principal Investigator. “But observational data from the real world is never this simple. When assessing the causal effects, interventions are often complex, they involve multiple actions simultaneously, and they are measured on a continuous scale. Data scientists require new methods and software tools that can meet the challenge of identifying cause when data is imperfect, messy, and influenced by many factors over time.”

The grant, totaling about $1 million, enables three collaborative projects led by faculty, each from a different Harvard school:

  • Francesca Dominici will lead the design of new methods for characterizing subpopulations that experience different causal effects of a given intervention.
  • Kosuke Imai, Professor of Government and of Statistics at the Harvard Faculty of Arts and Sciences, will lead the development of new methods to identify and estimate causal effects using data that vary in time and space.
  • Jose Zubizarreta, Associate Professor of Health Care Policy at Harvard Medical School, will lead work to improve experimental design in high-dimensional settings.

“I’m delighted to be a part of the group leading this critical charge,” says Imai. “We may come from three distinct areas of application, but our work shares common methodological challenges that, if overcome, can transform what data science can tell us about causes and effects in the world.”

Project teams will include graduate students, postdoctoral fellows, and data scientists from across the University, advised by a group of expert economists including Carl Morris (Harvard), Joseph Newhouse (Harvard), David Cutler (Harvard), and Anup Malani (University of Chicago). “I’m looking forward to what we’ll learn not only from our collaborators and advisors, but also from the students and postdocs with whom we’ll be working,” says Zubizarreta. “They are innovative and creative beyond imagining.”

The HDSI will serve as a convener and coordinator for the project, including creating outlets for the greater data science community to access emerging results. “Uniting and amplifying these types of methodological advances across varied application domains is precisely what the HDSI aims to achieve,” Dominici shares. “We’re incredibly grateful for the Sloan Foundation’s investment in this work.”

About the Harvard Data Science Initiative

The Harvard Data Science Initiative was launched in 2017 to connect data science efforts across Harvard University’s numerous schools and research centers. It combines and coordinates diverse technical and domain expertise to ignite moonshot initiatives and drive scientific, economic, and social progress. Through its research and education initiatives the HDSI revolutionizes and amplifies data-driven approaches to creating new knowledge for the world.

See also: Featured