Data Science Institute Transitions to University-wide Research Center

Kathy McKeown
Jeannette Wing

With five productive and impactful years coming to a conclusion, the Data Science Institute (DSI), launched at Columbia Engineering, is transitioning to become a University-wide institute, under the leadership of Jeannette Wing, who is joining the University as the Armen Avanessians Director of Columbia’s Data Science Institute and Professor of Computer Science. Wing will lead the next phase of the Institute in its expanded role. Its Founding Director, Kathleen McKeown, the Henry and Gertrude Rothschild Professor of Computer Science, and its Founding Associate Director, Patricia Culligan, the Robert A.W. and Christine S. Carleton Professor of Civil Engineering, will conclude their two terms on June 30, 2017. 

Established in July 2012 as part of the New York City’s initiative to expand the City’s top-tier applied sciences and engineering campuses, the Data Science Institute has, under the leadership of McKeown and Culligan, rapidly emerged as an intellectual leader in both foundational and interdisciplinary data science, emphasizing the disruptive power of data science to solve some of today’s pressing societal challenges.

McKeown and Culligan
Top: Kathy McKeown; Bottom: Patricia Culligan
—Photos by Jeffrey Schifman

McKeown and Culligan have established Columbia’s reputation as a leader in data science and the DSI as a world-class, interdisciplinary institute that is recognized both nationally and internationally among the top research centers in this field. Together, they have defined and furthered foundational data science and fostered its transformative impact on other academic areas by spearheading highly interdisciplinary collaborations across schools in both research and education. The Institute has also emerged as a vital forum for discussions on important issues such as data privacy, transparency, and security.

More than 30 new faculty members – including 20 in Engineering – have been hired in cross-cutting data science research areas, while over 200 faculty members and researchers from 11 schools across Columbia’s campus are engaged and collaborating to exploit data in areas ranging from business to medicine, social work to literature, history to policy, and engineering to the natural sciences, among many others.

DSI initiated new cross-cutting research collaborations in part through funding from the Moore and Sloan Foundations and through the ROADS seed funding provided by the Provost’s Office. Research has been further facilitated through proposal support for government and industry research funding.

DSI has also launched an impressive number of new educational offerings that provide learning opportunities to students both within and outside the University community. Among these are a new Master’s program in Data Science, a MOOC on Data Science and Analytics in Context offered through Columbia X, and the Collaboratory@Columbia, a University-wide program created in partnership with Columbia Entrepreneurship to propel data science education for Columbia students across campus by bringing the impact of data science to their particular fields. Deeply integrated with the local, national, and global technology industry through its thriving Industry Affiliates program, the DSI has helped launch many successful start-ups and has worked effectively to deepen and extend relationships with New York City’s government.

Through McKeown and Culligan’s strong leadership, there are now extraordinary opportunities for Columbia to be at the forefront of harnessing the power of today’s data-rich world to propel discovery and to translate research into action for the public good. In its next phase as a University-wide research center, the Data Science Institute will span the breadth and depth of knowledge that exist across the campuses to bring data science to bear on the solution of global challenges, to re-imagine scholarly fields as they are revolutionized by data science, and to spearhead new cross-disciplinary educational offerings in data science that can meet the needs of a multitude of different disciplines.

—by Joanne Hvala

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