Скачать или смотреть PINNs for Optimization and Control

Automated Systems & Soft Computing Lab (ASSCL), under the guidance of the College of Computer and Information Sciences (CCIS), invites you to attend the keynote speech entitled: "Physics-Informed Deep Learning for Optimization and Control"
Presented by: John Hedengren, Professor in the Department of Chemical Engineering, Brigham Young University, USA

Prof. John Hedengren leads the Process Research and Intelligent Systems Modeling (PRISM) group at Brigham Young University with a focus on physics-informed machine learning for optimization of energy systems. He received his doctorate degree from the University of Texas at Austin and worked as a consultant and senior engineer for 7 years on advanced control and optimization for polymers. His work includes the Python GEKKO optimization suite that is downloaded 10,000 times per month. He led the development of the Arduino-based Temperature Control Lab that is used by 70 universities for process control education. His 85 publications span topics of data science, machine learning, smart grid optimization, unmanned aerial systems, and predictive control. He teaches online courses on machine learning, data science, advanced control, and introduction to engineering programming that are accessed by 30,000 students each week. He served as a Distinguished Lecturer for the Society of Petroleum Engineers in 2018-2019. He is the recipient of the 2014 David Himmelblau award and the 2018 Computing Practice award from the American Institute of Chemical Engineers CAST Division.