Cornell University launches $1.5M Center for Data Science for Improved Decision Making

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Cornell University launched the Center for Data Science for Improved Decision Making, a center focused on the research of data management systems that handle data responsibly and are used for the public benefit.

A team of Cornell computer scientists, statisticians and mathematicians have formed the Center for Data Science for Improved Decision Making to research data management systems that handle data responsibly and are used for the public benefit.

Their research will be supported by a $1.5 million grant from the National Science Foundation’s TRIPODS (Transdisciplinary Research in Principles of Data Science) program.

The center will focus on several topics including:

  • How to guarantee the privacy of data and ensure that decisions are not biased by race, gender or other characterizations. The researchers plan to explore systems that have the ability to detect and correct these weaknesses.
  • Learning about their structure and the processes that take place within social networks, where connections between people can be used to inform decision making and detect fake news.
  • Research “Interventions” that are based on users histories to make recommendations or suggestions. 
  • Uncertainty quantification: "Knowing how unsure a prediction might be", especially when applied to decision-making with potential consequences to human subjects. 
  • The ambiguity about Deep learning and what these systems actually learn.

The research group is integrated by Kilian Weinberger, associate professor of computer science; Jon Kleinberg, the Tisch University Professor of Computer Science; Steve Strogatz, the Jacob Gould Schurman Professor of Applied Mathematics; Giles Hooker, associate professor of biological statistics and computational biology; and David Shmoys, the Laibe/Acheson Professor of Business Management and Leadership Studies in the School of Operations Research and Information Engineering. The group plans to collaborate with other scientists in related fields.