Michael E. Glinsky, PhD

... about


Focus is on the application of techniques that integrate decision science, deep learning, machine learning, artificial intelligence, data science and Bayesian data analysis to make better business decisions. This includes imbedding physical constraints into the deep learning and outputting of the critical uncertainties need to make the better decisions. Part of this work mandates doing large numbers of parallel computations on large computer clusters, significant Python programming, and software architectural design.

Michael E. Glinsky received a B.S. degree in physics from Case Western Reserve University in 1983 and a Ph.D. degree in physics from the University of California, San Diego in 1991. His doctoral research on magnetized pure electron plasmas was recognized by the American Physical Society as the outstanding thesis in the United States (1993 Simon Ramo Award). Before enrolling in graduate school as a National Science Foundation Graduate Fellow, he worked as a geophysicist for Shell Oil Company. After graduate school, he worked as a Department of Energy Distinguished Postdoctoral Research Fellow at Lawrence Livermore National Laboratory.

His 30 year career has focused on the use of data science, deep learning and Bayesian data analysis to make better business decisions; as a technology creator, strategic thinker, and leader at major companies and laboratories (such as Royal Dutch Shell, BHP Billiton, Halliburton, CSIRO, LLNL, and Sandia National Laboratories), and was an adjunct faculty member in the Physics Department at University of Western Australia. He received the top Australian scientific medal for his research on petroleum reservoir characterization in 2004.

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