Gordon Kaufman is the Morris A. Adelman Professor of Management, Emeritus and a Professor of Statistics at the MIT Sloan School of Management.
Kaufman is a petroleum industry expert. His research focuses on primary energy resources, with particular attention to the process of discovering oil and gas. He has a long-standing interest in Bayesian econometrics and multivariate analysis as well as in risk analysis of complex strategic problems. Kaufman’s current research interest is how to appraise uncertainties within large systems whose components are logically related in complex ways—such as global climate change models and their impacts, nuclear reactor fault trees, and Bayesian networks—when experts provide incomplete information about these uncertainties.
Kaufman holds a BS in industrial engineering and electrical engineering from Yale University and an MBA and a DBA from Harvard University.
Kaufman, Gordon M., Ricardo A. Olea, and R. Faith. Mathematical Geosciences. Forthcoming.
"Properties of Successive Sample Moment Estimators."
Barouch, E., S. Chow, G. Kaufman, and T. Wright, Working Paper. 1985.
"Oil and Gas Discovery Modelled as Sampling Proportional to Random Size."
Barouch, E., and G. Kaufman, Working Paper. 1976.
"On Sums of Lognormal Random Variables."
Barouch, E., and G.M. Kaufman, Working Paper. 1976.
"Bayesian Factor Analysis."
Kaufman, G., and J. Press, Working Paper. 1973.
Kaufman, Gordon M. In Handbook of Mathematical Geosciences: Fifty Years of IAMG, edited by B.S. Daya Sagar, Frits Agterberg, and Qiuming Cheng, 105-115. Cham, Switzerland: Springer International Publishing,