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Professor Burnap’s work focuses on how companies can improve product management and product design using tools from machine learning and big data.

His research interests include: (1) quantifying consumer needs and converting them to product features, (2) understanding market structure and new product opportunities using big data, and (3) improving product decisions by accounting for engineering and design feasibility.

Prior to joining Yale, he worked in product research at General Motors, and in consulting for a variety of startups and enterprise firms.  He completed his postdoc at MIT Sloan, Ph.D. Design Science and M.S. Mechanical Engineering at Michigan, and B.S. Engineering Physics at UIUC.


  • PhD, University of Michigan, 2016
  • MS, University of Michigan, 2013
  • BS, University of Illinois, Urbana-Champaign, 2011

Selected Works

Working Papers