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John Hedengren

Associate Professor at Brigham Young University in the Chemical Engineering Department. He leads the BYU Process Research and Intelligent Systems Modeling (PRISM) group with a current focus on structured machine learning for optimization of energy systems, unmanned aircraft, and drilling. Prior to BYU he worked in industry for 7 years on nonlinear estimation and predictive control for polymers. His work includes the APMonitor Optimization Suite with a recent extension to the Python GEKKO language. He led the development of the Arduino-based Temperature Control Lab that is currently used by 40 universities for process control education. His 47 publications span topics of oil production, drilling automation, smart grid optimization, unmanned aerial systems, and nonlinear predictive control. His professional service includes an appointment as an adjunct professor at the University of Utah, Section EiC for the Processes Journal, and member of the AIChE CAST Executive Committee (Webinar Editor). In 2005, he received a Ph.D. (Ch.E.) from the University of Texas at Austin for contributions to control and estimation of large-scale dynamic systems.

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