From molecules to organs, formulas to models
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Babatunde Ogunnaike

Babatunde Ogunnaike

Department of Chemical Engineering
University of Delaware

Doctorate–1981 University of Wisconsin-Madison
Masters (Statistics)–1981 University of Wisconsin-Madison
Bachelors–1976 University of Lagos, Nigeria

Our research efforts are organized around the general theme of first understanding the dynamic behavior of complex systems through mathematical modeling and analysis, and then exploiting this understanding for novel designs and improved operation. The particular complex systems of interest range from polymer reactors, particulate processes and extruders, to biological systems on the cellular, tissue, and organ levels. When sufficient fundamental knowledge is available, we develop and employ dynamic “mechanistic” models; when more data is available than fundamental knowledge, we apply probability theory and statistics for efficient data acquisition and “empirical” model development. Our research group has three main areas of focus:

  • Control and systems theory, where we are concerned with the development of effective control techniques, with application to industrial polymer reactors, distillation columns, particulate processes, and reactive extrusion processes; we are also interested in reverse engineering biological control systems for process applications.
  • Systems biology, where we bring principles of control and systems theory as well as probabilistic/statistical techniques to bear on the analysis of biological processes. We are developing models, tools and techniques to study biological systems across various levels of granularity—from the molecular level where mechanistic details at the genetic and protein levels are studied, to the cellular, tissue, organ and physiological system level. The goals of our systems biology efforts are to be able to understand, analyze and predict integrated biological systems function with sufficient fidelity for potential practical medical and pharmaceutical applications.
  • Product engineering, Process design and operations, where we employ both stochastic and deterministic techniques for engineering desired characteristics into products, and subsequently for developing inherently robust processes to manufacture these products to meet customer demands consistently in the face of unavoidable process and raw material variations.

Selected Publications
V. Mikkilineni, R.D. Mitra, J.R. DiTonno, J. Merritt, G.M. Church, B.A. Ogunnaike, and J.S. Edwards, “Digital quantitative measurements of gene expression,” Biotech. and Bioeng., 86, 117-124, 2004.

N. Hernjak, F. J. Doyle, III, B. A. Ogunnaike, and R. K. Pearson, "Chemical Process Characterization for Control Design", in Integration of Design and Control, edited by P. Seferlis and M. Georgiadis (Elsevier 2004)

N. Zambare, M. Soroush and B.A. Ogunnaike, "A method of robust multi-rate state estimation", J. Process Control, 13, 337 (2003)

N. Mehranbod, M. Soroush, M. Piovoso and B. A. Ogunnaike, "A probabilistic model for sensor fault detection and identification", AICHE J. (2003)

F. J. Doyle, R. K. Pearson, and B. A. Ogunnaike Identification and Control Using Volterra Models, (Springer, London 2002)

Chemical Process Control VI, edited by J. B. Rawlings, B. A. Ogunnaike and J. W. Eaton (CACHE American Institute of Chemical Engineers, N.Y. 2002)

H. Perez, B. Ogunnaike and S. DeVasia, "Output tracking between operating points for nonlinear processes: Van de Vusse example", IEEE Transactions on Control Systems Technology, 10 (4), 611 (2002)

N. Zambare, M. Soroush, B. A. Ogunnaike, "Robustness improvement in multi-rate state estimation", Proc. Am. Control Conf., 2, 993-998 (2001)

J. D. Bomberger, D. E. Seborg, and B. A. Ogunnaike, "RBFN Identification of an Industrial Polymerization Reactor Model", in Application of neural networks and Other Learning Technologies in Process Engineering, edited by I. M. Mujtaba and M. A. Hussain (Imperial College Press, London 2001)

B. Wayne Bequette and B.A. Ogunnaike, "Chemical process control education and practice", IEEE Control Systems Magazine, 10-17 (2001)