How AI can better serve the chemical process industry
Years of production have accumulated rich data assets throughout the chemical process industry (CPI).
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The Authors
Lou, H. H. - Lamar University, Beaumont, Texas
Helen H. Lou is a Professor in the Dan F. Smith Department of Chemical Engineering at Lamar University in Beaumont, Texas. Her areas of expertise include big data analytics, machine learning and process systems engineering. She has been applying these technologies for the sustainable development of the chemical processing industry. Dr. Lou has successfully implemented more than 50 projects sponsored by federal, state and private sectors, and has published extensively. She earned her MA degree in computer science and her PhD in chemical engineering, and has trained 16 master’s-level and 9 doctoral-level chemical engineers, as well as influenced many undergraduate chemical engineers. Due to her outstanding achievements, Dr. Lou was elected as a Fellow of the American Institute of Chemical Engineers (AIChE) in 2018.
Gai, H. - Lamar University, Beaumont, Texas
Huilong Gai is a research scientist at Lamar University. He received his PhD in chemical engineering from Lamar University in 2019. His work focuses on the modeling and control of petrochemical processes and combustion kinetic modeling and control of industrial flares. Dr. Gai specializes in various machine-learning algorithms and first-principles models.
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