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Professor Burnap’s work focuses on helping companies improve product management and product design using tools from machine learning and big data. He specializes in developing generative AI targeting personalized products. His research interests include quantifying consumer needs by converting product features, understanding market structure for new product opportunities using big data, and improving product decisions by accounting for engineering design feasibility. Prior to joining Yale, he worked in product research at General Motors and consulted for startups and enterprise firms. He completed a postdoc at MIT Sloan and earned his Ph.D. in Design Science, M.S. in Mechanical Engineering from the University of Michigan, and B.S. in Engineering Physics from the University of Illinois, Urbana-Champaign.
Administered via the Graduate School of Arts and Sciences (GSAS). GRE General is optional for PhD.