Dr. Vassilios Tzouanas is an Assistant Professor of Control and Instrumentation in the Engineering Technology Department at the University of Houston-Downtown. Dr. Tzouanas earned a Diploma in Chemical Engineering from Aristotle University, the Master of Science degree in Chemical Engineering/Process Control from the University of Alberta, and the Doctor of Philosophy degree in Chemical Engineering/Process Control from Lehigh University. His research interests focus on process control systems, process modeling and simulation, artificial intelligence and expert systems. His professional experience includes management and technical positions with chemicals, refining, and consulting companies. He has published and presented a number of papers on advanced process control, real-time optimization systems, adaptive control, artificial intelligence and expert systems. He is a member of AIChE.

Education

Ph.D. in Chemical Engineering/Process Control, Lehigh University, PA, 1989.

M.Sc. in Chemical Engineering/Process Control, University of Alberta, AB, 1985.

Diploma in Chemical Engineering, Aristotle University, Greece, 1982.

Work History

Assistant Professor of Control and Instrumentation Engineering Technology, University of Houston-Downtown,
2010 – present.

Regional Technical Superintendent of Control Systems Engineering, Lyondell Chemical, 2006 - 2009.

Consulting Engineer of Control Systems Engineering, Lyondell Chemical, 1999 - 2006.

Staff Engineer, Project Manager and Technical Leader, AMOCO, 1996 - 1999.

Principal Control Systems Engineer, ARCO Chemical, 1994 - 1996.

Project Engineer to Lead Engineer, Setpoint Inc., 1990 - 1994.

Honors and Awards

Lyondell Corporate Award for Efficiency, 2006.

Amoco Technical Award, 1998.

Research Interests

My broad research interests focus on advanced multivariable process control, adaptive control, process modeling and simulation, artificial intelligence and expert systems. My overarching research goal is not simply to invent new knowledge but to also convert the feasible into practical. The result will be control systems that help optimize process operation (i.e. maximum return on investment) subject to operational excellence (i.e. safety, environmental, reliability, quality) constraints. Process examples are drawn from different industrial sectors such as chemicals, refining, bio-systems, and renewable energy.

Examples of current research efforts include:

• Multivariable and Adaptive Control: the objective is to design robust, multivariable, adaptive control systems and demonstrate their effectiveness on time varying processes such as transitioning of industrial scale polymerization reactors from one product to another or biological processes
• Process Modeling and Simulation: the objective is to design robust product quality inferential methods to predict infrequently measured product qualities when on-line measurements are infrequent or not available. Demonstrate effectiveness on industrial processes such as refining and petrochemicals.
• Artificial Intelligence and Expert Systems: the objective is to develop methods to help identify erroneous sensors used in feedback control loops or in making critical decisions. Use of expert systems, statistical methods, and data mining techniques may be employed. Data mining is the process of extracting valid, previously unknown, comprehensible and actionable information from large databases and using it to make business decisions.  Expert system techniques and pattern recognition can be used for fault signal detection. Statistical methods can be employed to screen data for possible errors (e.g. standard deviation, drifting from nominal values per current process operation). 
• Semi-Autonomous Systems: the objective is to develop technologies that improve process safety during abnormal process operating conditions and demonstrate their effectiveness during the startup/shutdown of major industrial processes such as polymerization reactors or ethylene plants.

• Tzouanas, V.K., “A New Course on Process Design and Operation in an Engineering Technology Program”, in proceedings of ASEE Annual Conference, Vancouver, CA, June 26-29, 2011.
• Tzouanas, V.K. and Campbell, L., “The Teamwork Conundrum:  What Should be Taught and How Can We Assess Student Learning in Engineering Technology?”, in proceedings of ASEE Annual Conference, Vancouver, CA, June 26-29, 2011.
• Tzouanas, V.K., Alvarado, J. and Cadena, S., “Introducing and Teaching a New Course on Process Design and Operation in an ET Program”, in proceedings of  ASEE-CIEC Conference ASEE-GSW Conference, Houston, TX, March  2011.
• Tzouanas, V.K. and Alvarado, J., “Experiential Learning from Teaching a Senior Level Process Control Course in an ET Program”, in proceedings of  ASEE-CIEC Conference,  San Antonio, TX, February 2011.
• Rickard, K.,Tzouanas, V.K., Wissner, M., Arman, T., Matthews, E., Gopalakrisnan, M., Montgomery, G., Ferguson, T., Kelly, T., Ye, N., Ayala, J. “Some Key Issues on a Successful Application of Real Time Optimization System to an Ethylene Plant”, AIChE 2007 Spring EPC, April 2007.
• Tzouanas, V.K., Price R., Biesman R., Meziou Z., and Caldwell J., “Advanced Process Control of a HDPE Plant”, AspenWorld 2002, Washington, DC, October, 2002.
• Tzouanas, V.K. and Martin D.E., "Application of SAMPLES to Product Quality Prediction", Annual AIChE Meeting, San Francisco, November 1994.
• Tzouanas, V.K., Luyben, W.L., Georgakis, C. and Ungar, L.H., "Expert Multivariable Control, Part I: The General Structure and Design Methodology", Ind. Eng. Chem. Res., Vol. 29, No. 3, pp. 382 - 389, 1990.
• Tzouanas, V.K., Luyben, W.L., Georgakis, C. and Ungar, L.H., "Expert Multivariable Control, Part II: Application to Two Product Distillation Columns", Ind. Eng. Chem. Res., Vol. 29, No. 3, pp. 389 - 403, 1990.
• Tzouanas, V.K., Luyben, W.L., Georgakis, C. and Ungar, L.H., "Expert Multivariable Control, Part III: Extension to Three Product Sidestream Distillation Columns", Ind. Eng. Chem. Res., Vol. 29, No. 3, pp. 404 - 415, 1990.
• Tzouanas, V.K., Luyben, W.L., Georgakis, C. and Ungar, L.H., "Application of the Expert Multivariable Controller to Distillation Columns", Annual AIChE Meeting, San Francisco, November 1989.
• Tzouanas, V.K. and Shah, S.L., "Adaptive Pole-assignment Control of Processes with large Time Delays", International Journal of Systems Science, Vol. 21, Issue 6, pp. 1121 - 1134, 1990.
• Tzouanas, V.K. and Shah, S.L., "Adaptive Pole-assignment Control of a Batch Polymerization Reactor", Chemical Engineering Science, Vol. 44, No. 5, pp. 1183 - 1193, 1989.
• Tzouanas, V.K., Georgakis, C., Luyben, W.L and Ungar, L.H., "Expert Multivariable Control", Computers and Chemical Engineering, Vol.12, No. 9/10, pp. 1065 - 1075, 1988.
• Tzouanas, V.K. and Lidie, S.O., "Interfacing a Symbolics LISP Machine with the Cyber", Computing at Lehigh, Vol. XV, No. 5, May 1988.
• Tzouanas, V.K., Georgakis, C., Luyben, W.L and Ungar, L.H., "Expert Multivariable Control", paper presented at the Annual AIChE Meeting, New York, N.Y., November 1987.
• Ungar, L.H., Tzouanas, V.K. and Georgakis, C., "Knowledge-based Expert Systems for Process Control", AIChE Meeting, New Jersey Chapter, October, 1987.
• Tzouanas, V.K., Ungar, L.H. and Georgakis, C., "Towards an Expert Multivariable Controller", Proc. 10th IFAC World Control Congress, Vol. 6, pp. 357 - 362, Munich, Germany, July 1987.
• Tzouanas, V.K., "Real-time Expert System Control of Chemical Processes", Regional Symposium for Artificial Intelligence in Fundamental and Applied Research, Philadelphia, PA, January 1987.
• Tzouanas, V.K. and Shah, S.L., "Adaptive Pole-placement Control of a Batch Polymerization Reactor", Proc. IFAC Conference on Adaptive Control of Chemical Processes, pp. 114 - 119, Frankfurt, Germany, 1985.