Data-Driven Model Estimation from Observed Equilibria: What transportation networks and bacterial cells have in common?
Director of the Center for Information and Systems Engineering
Friday, May 5, 2017
Brickyard Engineering (BYENG) 210, Tempe campus [map]
Hosted by Ted Pavlic
Equilibrium modeling is common in a variety of fields such as game theory, transportation science, and cell metabolism. The inputs to these models, however, are often difficult to estimate, while their outputs, i.e., the equilibria they are meant to describe, are often directly observable. By combining ideas from inverse optimization with the theory of variational inequalities, Paschalidis will present an efficient, data-driven technique for estimating the parameters of these models from observed equilibria. His framework allows for both parametric and non-parametric estimation and provides probabilistic guarantees on the quality of the estimated quantities.
He will present applications in two seemingly distinct areas. In transportation networks we use these techniques to estimate the congestion function, which determines users’ route selection. Using actual traffic data from the Boston area, they can assess the inefficiency of drivers’ selfish behavior vs. a socially optimal solution, also called the price of anarchy.
In biochemical networks, Flux Balance Analysis (FBA) is a widely used predictive model which computes a cell’s steady-state chemical reaction fluxes as a solution to an optimization problem. FBA, however, assumes a certain global cellular objective function which is not necessarily known. They will use their new method to estimate such an objective. This enables them to elucidate the cellular metabolic control mechanisms and infer important information regarding an organism’s evolution
Yannis Paschalidis is a Professor of Electrical and Computer Engineering, Systems Engineering, and Biomedical Engineering at Boston University. He is the Director of the Center for Information and Systems Engineering (CISE). He obtained a Diploma (1991) from the National Technical University of Athens, Greece, and an M.S. (1993) and a Ph.D. (1996) from the Massachusetts Institute of Technology (MIT), all in Electrical Engineering and Computer Science. He has been at Boston University since 1996. His current research interests lie in the fields of systems and control, networks, optimization, operations research, computational biology and medical informatics.
Prof. Paschalidis’ work has been recognized with a CAREER award (2000) from the National Science Foundation, the second prize in the 1997 George E. Nicholson paper competition by INFORMS, the best student paper award at the 9th Intl. Symposium of Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt 2011) won by one of his Ph.D. students for a joint paper, an IBM/IEEE Smarter Planet Challenge Award, and a finalist best paper award at the IEEE International Conference on Robotics and Automation (ICRA). His work on protein docking (with his collaborators) has been recognized for best performance in modeling selected protein-protein complexes against 64 other predictor groups (2009 Protein Interaction Evaluation Meeting). His recent work on health informatics won an IEEE Computer Society Crowd Sourcing Prize. He was an invited participant at the 2002 Frontiers of Engineering Symposium organized by the National Academy of Engineering, and at the 2014 National Academies Keck Futures Initiative (NAFKI) Conference. Prof. Paschalidis is a Fellow of the IEEE and the Editor-in-Chief of the IEEE Transactions on Control of Network Systems.