SYSTEMS RESEARCH INSTITUTE
for Chemical and Biological Processes
As of December 31, 2022, Professor Georgakis retired from teaching duties.
Tufts University organized a Celebration of his Career on June 2, 2023.
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See HERE the detailed program, along with video clips of the presentations.
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The Systems Research Institute (SRI) for Chemical and Biological Processes, established in 2004, fosters Industry-University research collaborations that seek to invent new and novel Process Modeling, Optimization, and Control methodologies that strongly influence industrial practice.
Mission
- Foster innovating projects in data-driven modeling, optimization, and control of chemical and biological processes;
- Establish collaborations with leading national and international researchers in Universities and Industry;
- Influence industrial research and practices
Industrial Collaborations
The Institute’s research activities on Data-Driven Modeling (DDM) of chemical and pharmaceutical processes have included the collaboration of researchers from several leading companies. The list includes researchers from Biogen, Dow, ExxonMobil, Merck, Pfizer, and Sunovion Pharmaceuticals. Many of these collaborations have resulted in significant research publications over the last ten years. Additionally, several academic collaborations are presently active. More information on our collaborations can be found here.
Research Breakthroughs
The two most important research breakthroughs generalize the Design of Experiments methodology on two fronts. They suggest how to use Machine Learning (ML) algorithms to Process Systems Engineering (PSE) problems. They generalize the classical Design of Experiments (DoE) methodology by incorporating dynamic factors and modeling time-resolved output measurements. The first generalization is called the Design of Dynamic Experiments (DoDE) while the second is called the Dynamic Response Surface Methodology (DRSM). They both have fueled an explosion of industrial and university collaborations. Read more information here.
Novel Solutions to Important Challenges
- Discovery of the active stoichiometry in a reaction mixture; more.
- Estimation of Surrogate Models; more.
- Non-Linear Sensitivity; more.
For more technical information, please visit the main page of our research activities, here.