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Message Archive



Thursday, October 15, 2015

 

This email is being sent to all members of the Baruch College faculty.

For an archive of announcements sent from the Associate Provost beginning June 2011, click here.

 

 

The Predictive Power of Massive Data about our Fine-Grained Behavior
Professor Foster Provost
New York University

Monday, October 19, 12:45pm, NVC 14-285

 

From: Professor Radhika Jain, Computer Information Systems

Our first speaker of the semester in the Analytics seminar series is Professor Foster Provost from NYU. Please see below for the details of the talk. Please forward and share this with your colleagues.

The Predictive Power of Massive Data about our Fine-Grained Behavior
What really is it about Big Data that makes it different from traditional data?  In this talk I illustrate one important aspect: massive ultra-fine-grained data on individuals' behaviors holds remarkable predictive power.  I examine several applications to marketing related tasks, showing how machine learning methods can extract the predictive power and how the value of the data "asset" seems different from the value of traditional data assets.  I then dig deeper into the predictions to show that the fine-grained data incorporates various sorts of information that we traditionally have sought to capture by other means (demographics, psychographics, category interest, purchase intent).  Finally, I discuss the flip side of the coin: the remarkable predictive power based on fine-grained information on individuals raises new privacy concerns, but also may present novel solutions such as a privacy "cloaking device."

Bio: Foster Provost
Foster Provost is Professor of Data Science, Professor of Information Systems, Andre Meyer Faculty Fellow and Interim Director of the Center for Data Science at New York University. He is coauthor of the best-selling book, Data Science for Business. His research focuses on modeling behavior data, modeling (social) network data, crowd-sourcing for data science, aligning data science with application goals, and privacy-friendly methods. His research has won many awards, including the INFORMS Design Science Award and best paper awards at KDD across three decades. He cofounded several data-science-oriented companies based on his research, including Dstillery and Integral Ad Science. Foster previously was Editor-in-Chief of the journal Machine Learning. His latest music album, Mean Reversion, is scheduled to be released later this year.

 

For more information, please contact Prof. Radhika Jain at Radhika.Jain@baruch.cuny.edu