Babatunde A. Ogunnaike William L. Friend Chaired Professor of Chemical Engineering; Dean, College of EngineeringUniversity of Delaware

OPTIMIZING IN-VITRO FERTILIZATION TREATMENT A Pedagogical Case Study in Random Phenomena Analysis with Social ImplicationsEngineering practice has always required involvement in the acquisition, analysis, interpretation and exploitation of data in one form or another, so that the "well-educated" engineer ought to be truly conversant with how to handle data. This is even more so today, with many engineers now working in non-traditional areas ranging from molecular biology to finance, and the problems to be solved continuing to widen in scope and becoming more interdisciplinary. While most engineers are traditionally well-trained in problem formulation and problem solving when all the entities involved are considered deterministic in character, many remain uncomfortable with problems involving random variations, if such problems cannot be idealized and reduced to the more familiar "deterministic" types. Ironically, while students of generations gone by were trained in basic data analysis, most of today's students are not. And for the very few that receive any form of training in probability and statistics, most tend to perceive such training more as a set of instructions on what to do and how to do it, than as a training in fundamental principles of random phenomena.

At the University of Delaware, the course in "Random Phenomena" is taught by presenting basic fundamental principles, methods, and tools for formulating and solving engineering problems that involve randomly varying phenomena. The premise is that by emphasizing fundamentals and basic principles, and then illustrating these with examples, the student will be better equipped to deal with a range of problems wider than that explicitly covered in class. In this presentation, we discuss a particular case study that is used in this class as a pedagogical tool to illustrate how to solve complex, real-life problems involving randomly varying phenomena. It demonstrates how the mathematics of probability, probability models, statistical data analysis, model validation, and mathematical optimization can be used effectively to answer a central question in in-vitro fertilization (IVF) treatment: how many embryos should be implanted to maximize the chances of success while simultaneously minimizing the chances of multiple births?

Biography

The Ogunnaike group is interested in understanding the dynamic behavior of complex systems through mathematical modeling and analysis, and then exploiting this understanding for postulating novel designs and improved operation. Specific systems of interest range from polymer reactors, particulate processes and extruders, to biological processes at the cellular and physiological levels. Specific research topics include modeling and control of industrial processes (polymer reactors, extruders, distillation columns); the application of process analytical technology for control of pharmaceutical processes; modeling and control of hybrid renewable energy systems; biological control systems; and systems biology with application to neuronal responses and cancer.

Dr Ogunnaike is the author or co-author of more than 100 peer-reviewed publications, and four books including a widely used textbook, Process Dynamics, Modeling and Control, published in 1994 by Oxford University Press, and Random Phenomena: Fundamentals of Probability and Statistics for Engineers, published in 2009 by CRC Press. He is an Associate Editor of the journal Industrial and Engineering Chemistry Research. His awards include the American Institute of Chemical Engineers 1998 CAST Computing Practice Award, the 2004 University of Delaware's College of Engineering Excellence in Teaching award, the 2007 ISA Eckman Award, and the 2008 AACC Control Engineering Practice award. He was named a fellow of the American Institute of Chemical Engineers (AIChE) in 2009, and elected a fellow of the Nigerian Academy of Engineering in 2012, of the US National Academy of Inventors in 2014. He is a 2016 fellow of the American Association for the Advancement of Science (AAAS) and a 2017 fellow of International Federation of Automatic Control (IFAC). He was elected to the US National Academy of Engineering in 2012.