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.
- Ron Cody, EdD, a retired professor from the Robert Wood Johnson Medical School now works as a private consultant and a national instructor for SAS Institute.
- Oliver Schabenberger, PhD, is Executive Vice President and Chief Technology Officer at SAS, shaping the vision for R&D employees worldwide
- Gerhard Svolba, Ph.D. is a product manager and pre-sales consultant at SAS Institute Inc. in Austria, where he specializes in Analytics and customer intelligence
- Richann Watson is an independent statistical programmer and CDISC consultant based in Ohio. She has been using SAS since 1996 with most of her experience being in the life sciences industry. She specializes in analyzing clinical trial data and implementing CDISC standards.