Vortrag von Prof. Serkan Gugercin

12. Dezember 2022

--- Title: Rational Interpolation from Data with Applications to Nonlinear Eigenvalue Problems

Zeit: 12. Dezember 2022
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Prof. Serkan Gugercin
Department of Mathematics
Virginia Polytechnic Institute and State University
Blacksburg, VA, USA


Monday 2022-12-12 1 p.m.
IST Seminar Room 2.255 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen



We start by studying the model reduction problem from a rational interpolation perspective and revisit some key findings such as the optimal rational interpolation in the H2-norm and rational-interpolants from data using the Loewner framework. We then study the concept of the Barycentric form of rational interpolants and show extensions to parametric dynamical systems.  If time allows, we  will also visit  nonlinear eigenvalue problems (NLEVPs), more specifically the contour-based techniques for NLEVPs and show that these techniques for NLEVPs have strong connections to the classical realization theory such as the Ho-Kalman algorithm. Once this connection is established, we then develop, using the Loewner-based rational interpolation theory, a systems-theory inspired  framework for solving NLEVPs. 


Biographical Information

Serkan Gugercin is a professor of Mathematics at Virginia Tech. He holds the Class of 1950 Professorship. He is also a core faculty member and a Deputy Director in the Division of Computational Modeling and Data Analytics. In 1992, he received his B.S. degree in Electrical and Electronics Engineering from Middle East Technical University, Ankara, Turkey; and his M.S. and Ph.D. degrees in Electrical Engineering from Rice University, in 1999 and 2003, respectively. His primary research interests are model reduction, data-driven modeling, numerical linear algebra, approximation theory, and systems and control theory.

Dr. Gugercin received the Ralph Budd Award for Research in Engineering from Rice University in 2003 for the best doctoral thesis in the School of Engineering; Teaching Award from Jacobs University Bremen, in 2003; the National Science Foundation Early CAREER Award in Computational and Applied Mathematics in 2007; and the Alexander von Humboldt Research Fellowship in 2016.


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