Dr. Christos Georgakis is a Professor of Chemical and Biological Engineering at Tufts University and the Bernard M. Gordon Senior Faculty Fellow in Systems Engineering. Starting in 1975, he served as du Pont Assistant Professor and Edgerton Associate Professor of Chemical Engineering at MIT, and as Professor of Measurement and Control at the University of Thessaloniki in Greece. He joined Lehigh University in 1983 where he founded and directed for almost 20 years the Chemical Process Modeling and Control Research Center and its associated industrial consortium. Lehigh University honored him in 2001 with the Iacocca Professorship in Engineering. Between 2002 and 2004 he was the Othmer Distinguished Professor of Chemical Engineering at the Polytechnic University, in New York City and joint Tufts in 2004. In the middle 1990s, Professor Georgakis also served for three years as a Visiting Professor at Delft University in the Netherlands.
He was awarded in 1978 a Dreyfus Foundation Teacher-Scholar Grant. In 1998 one of his publications was selected for the O. Hugo Schuck Best Paper Award of the American Automatic Control Council. In 2001 he was the recipient of the Computing Award of the CAST Division of the American Institute of Chemical Engineers. He became a fellow of the American Institute of Chemical Engineer 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 has served as the Chair of the Technical Committee on Process Control and as the Chair of the Coordinating Committee on Industrial Applications of the International Federation of Automatic Control (IFAC). In 2002-03 he served as the President of the American Automatic Control Council.
He is actively involved in consulting activities with a variety of companies in the area of Process Modeling, Monitoring, Optimization and Control of Continuous and Batch Processes. He has recently introduced a generalization of the classical Design of Experiments (DoE) methodology for dynamitic processes (continuous and batch) and named it Design of Dynamic Experiments (DoDE). This generalized methodology is expected to greatly facilitate the data-driven modeling of batch and continuous processes.