Michael L. Thompson
Research Fellow, The Procter & Gamble Company
Michael L. Thompson leads technical capability development applying Bayesian Machine Learning in the Procter & Gamble Company, R&D, Data & Modeling Sciences department. His degrees are in Chemical Engineering: B.S., Northwestern University, ’82; M.S., MIT, ’84; and Ph.D., MIT, ’96, with minor in Statistics and Artificial Intelligence. He has extensive experience in the process industry, having worked for Dow, Alcoa, Amoco, and Mitsubishi Chemical (Japan). Since joining P&G in 1999, Michael has applied his expertise in Bayesian Analysis, especially Bayesian networks, to deliver results spanning business functions including R&D, engineering, manufacturing, marketing, and business analytics. He has authored journal articles ranging from fluidized bed reactors to hybrid probabilistic and first-principles biochemical models to optimal consumer product design.