Research/Areas of Interest:
Data-Driven Modeling, Optimization, and Control of Batch Processes using Machine Learning algorithms, Model Predictive, Nonlinear and Plant-Wide Control, Statistical Process Monitoring, The Interaction between Process Design and Control, Modeling and Optimization of Pharmaceutical Processes
Ph.D., University of Minnesota, United States, 2021
M.S., University of Illinois at Chicago, Chicago, United States, 1972
Ch.E. Diploma, National Technical University of Athens, Athens, Greece, 1970
Christos Georgakis' present research activities focus on the development of data-driven modeling methodologies with applications in both batch and continuous processes. As an initial step in this direction, Georgakis has defined a generalization of the Design of Experiments (DoE) methodology for dynamic processes, which he called "Design of Dynamic Experiments (DoDE)." A second generalization called "Dynamic Response Surface Methodology" (DRSM) enables the modeling of time-resolved data from a set of DoE or DoDE experiments.
He became a fellow of the American Institute of Chemical Engineers in 1998, a fellow of the American Association for the Advancement of Science in 2004, and a fellow of the International Federation of Automatic Control (IFAC) in 2007. He served as President of the American Automatic Control Council, 2002-03.