Thomas A. (Tom) Badgwell
THE VERY BRIGHT FUTURE OF CHEMICAL PROCESS CONTROL
Thomas A. (Tom) Badgwell is Chief Technology Officer at Collaborative Systems Integration, an Austin-based startup providing systems integration services and software products for Open Process Automation (O-PAS) based systems.
He earned a BS degree from Rice University and MS and PhD degrees from the University of Texas at Austin, all in Chemical Engineering. Tom’s career has focused on modeling, optimization, and control of chemical processes, with past positions at Setpoint, Fisher/Rosemount, Rice University, Aspen Technology, and ExxonMobil.
He is a Fellow of the American Institute of Chemical Engineers (AIChE) and a past Director of the Computing and Systems Technology (CAST) Division, from which he received the Computing Practice Award in 2013. He has served as an Associate Editor for the Journal of Process Control and as a Trustee of the Computer Aids in Chemical Engineering (CACHE) Corporation. He currently serves as Vice-Chair of the IFAC Technical Committee TC 6.1 Chemical Process Control in Industry.
RECURRENT NEURAL NETWORKS FOR CONTROL – WHY, WHEN, HOW
Riccardo Scattolini was born in Milano, Italy, in 1956.
He received the Laurea degree in Electrical Engineering from Politecnico di Milano in 1979. In 1982 he spent one year in industry working on the simulation and control of petrochemical plants. From 1983 he held research and academic positions at the Università di Pavia and the Politecnico di Milano. Since 1994 he is full professor of Automatic Control. During the academic year 1984/85 he was visiting researcher at the Department of Engineering Science, Oxford University. In 1991 he was awarded the Heaviside Premium of the Institution of Electrical Engineers, United Kingdom.
He has been Associate Editor of the IFAC journal Automatica and of the International Journal of Adaptive Control and Signal Processing, and he has been member of the IPC and Editor at Large of several International Conferences. He has been contributing to Control Theory mostly in the areas of Model Predictive Control, distributed control and estimation, process modeling, identification, and control.
He is author of more than 120 scientific papers published in the main international journals on control and of more than 170 papers presented at international conferences.
FROM TIME-DRIVEN TO CONDITION-DRIVEN: WIDE-RANGE NONSTATIONARY INDUSTRIAL PROCESS MONITORING
Chunhui Zhao obtained her PhD degree in Control Science and Engineering from the University of Northeastern, China, in 2009.
From 2009 to 2012, she was a Postdoctoral Fellow with the Hong Kong University of Science and Technology and the University of California, Santa Barbara, Los Angeles, CA, USA.
She has been a Professor with College of Control Science and Engineering, Zhejiang University, Hangzhou, China.
Her research interests include statistical machine learning and data mining for industrial application. She has authored or coauthored more than 140 papers in peer-reviewed international journals, published two monographs and authorized 40 patents.
She has hosted more than 20 scientific research projects, including national and enterprise cooperation projects. She is now an IEEE senior member and has served Senior Editor of Journal of Process Control, AEs of two International Journals, including Control Engineering Practice and Neurocomputing.