Henry Bequet
Director of High Performance Computing and Machine Learning in the Financial Risk division, SAS
Henry Bequet is Director of High Performance Computing and Machine Learning in the Financial Risk division of SAS. In that capacity, he leads the development of a high-performance solution that can run SAS code on thousands of CPU and GPU cores for advanced models that use techniques like Black-Scholes, Binomial Evaluation, and Monte-Carlo simulations. Henry has more than 35 years of industry experience and 15 years of high-performance analytics practice. He has published two books and several papers on server development and machine learning.
By This Author
Deep Learning for Numerical Applications with SAS®
By Henry G. Bequet
Dive into deep learning! Written by an expert in high-performance analytics, Deep Learning for Numerical Applications with SAS® introduces a new field: Deep Learning for Numerical Applications (DL4NA). It introduces deep learning concepts in SAS along with step-by-step techniques that allow you to easily reproduce the examples on your high-performance analytics systems. It also discusses the latest hardware innovations that can power your SAS programs from many-core CPUs to GPUs to FPGAs to ASICs.
Featured Authors
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Todd Case has been working in the pharmaceutical industry as a statistical programmer for over 20 years. He completed his MS in Epidemiology from Columbia University and has worked at Forest Laboratories (now Allergan), Genentech, Bristol-Myers Squibb, and Biogen. He currently works at Vertex Pharmaceuticals.
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Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. Bob received a PhD in statistics from the University of North Carolina at Chapel Hill and was a research statistician at General Motors Research Laboratories before joining SAS.
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Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.
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Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors.