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.