Bio

Professor Provost studies data science and its alignment with business problems.

His current main research interests are:

  • predictive analytics
  • mining ultra-fine-grained data on behavior and social connections
  • human+machine intelligence systems (including crowdsourcing for analytics and human-machine loops)
  • explaining the decisions made by complex systems
  • causal inference at massive scale
  • ethical implications of data science, including impacts on privacy and civil rights

Prof. Provost’s research has won numerous awards, including the ACM SIGKDD Test of Time Award, the Best European Research Paper Award (AIS & CIONET), Best Paper published in the journal Information Systems Research in 2015, Best Paper Awards at the top data science research conference, ACM SIGKDD, across three decades, the 2009 INFORMS Design Science Award for his work on Social Network-based Marketing Systems, IBM Faculty Awards for outstanding research in data mining and machine learning, a President’s Award from what’s now Verizon, and more.

Prof. Provost served as Editor-in-Chief of the journal Machine Learning from 2004-2010.

He was elected as a founding board member of the International Machine Learning Society. He is a member of the editorial board of the journal Data Mining and Knowledge Discovery. In 2001, he was program chair for the ACM SIGKDD conference. He was an organizer of the 2009 & 2010 Workshops on Human Computation (HCOMP), an organizer of the 2010 Workshop on Social Media Analytics (SOMA), and a founding organizer of the Workshop on Information in Networks (WIN) [2009-2015].

Prof. Provost co-founded several successful companies, including  Detectica, Dstillery (formerly Media6degrees), Integral Ad Science, and Everyscreen Media. He advises companies on data science and AI/ML strategy.

Professor Provost has served as an expert witness on cases involving data science. He also has advised the U.S. Government (National Science Foundation, NASA, DARPA, National Research Council, FTC, White House Office of Science and Technology Policy) on policy and investments in data mining research.

He has applied advanced technologies to a variety of business and government problems, including real estate tech, compliance analysis, digital advertising, targeted marketing, fraud detection, counterterrorism, network diagnosis, network monitoring, and customer contact management.

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