Kathrin Smetana

Assistant Professor

School: School of Engineering and Science

Department: Mathematical Sciences

Building: Peirce

Room: 304

Email: ksmetana@stevens.edu

Education
  • PhD (2013) University of Muenster (Mathematics)
  • MS (2008) University of Freiburg (Mathematics)
Research

Kathrin Smetana's research interests lie broadly in the areas of (probabilistic) numerical analysis and scientific computing. More precisely, her research focuses on the development and numerical analysis of multiscale, model order and dimension reduction methods and their application in engineering, computational earth sciences, and computational biology. Furthermore, Dr. Smetana is advancing randomized methods used in data science and in compressed sensing for the approximation of partial differential equations, including both the design of approximations and their probabilistic numerical analysis.

General Information

Dr. Smetana is a tenure-track assistant professor in the Department of Mathematical Sciences at the Stevens Institute of Technology. Before joining Stevens in January 2021, she was an assistant professor in the Department of Applied Mathematics at the University of Twente, the Netherlands. Prior to that Dr. Smetana worked as a postdoctoral associate in the group of Professor Mario Ohlberger in the Faculty of Mathematics and Computer Science at the University of Münster, Germany and in the group of Professor Anthony T. Patera in the Department of Mechanical Engineering at the Massachusetts Institute of Technology.

Experience

Stevens Institute of Technology, Department of Mathematical Sciences

01/2021-Present: Assistant Professor

University of Twente (Netherlands), Department of Applied Mathematics

05/2017-01/2021: Assistant Professor

University of Münster (Germany), Faculty of Mathematics and Computer Science

06/2015-05/2017: Postdoctoral Research and Teaching Associate (working with Professor Mario Ohlberger)

Massachusetts Institute of Technology, Department of Mechanical Engineering

06/2013-05/2015: Postdoctoral Research Associate (working with Professor Anthony T. Patera)



Professional Service
  • Advances in Continuous and Discrete Models: Theory and Modern Applications: Member of Editorial Board
  • GEM - International Journal on Geomathematics: Guest Editor
Honors and Awards

Professor De Winter Award for the best international publication written by a female Assistant or Associate Professor of the University of Twente, November 2018

Invited Participant, 20th German-American Kavli Frontiers of Science Symposium 2016

Professional Societies
  • SIAM – Society for Industrial and Applied Mathematics Member
Grants, Contracts, and Funds

"Comprehensive monitoring and prediction of seismicity within the Groningen gas field using large scale field observations" Jeannot Trampert (PI, Utrecht University), Kathrin Smetana (Stevens Institute of Technology), Marie-Colette van Lieshout (CWI, University of Twente), Hanneke Paulssen (Utrecht University), NWO, 1500000 Euros, 2/1/2019-28/2/2024.

Selected Publications
Book Chapter
  1. Buhr, A.; Iapichino, L.; Ohlberger, M.; Rave, S.; Schindler, F.; Smetana, K. (2020). Localized model reduction for parameterized problems, book chapter in P. Benner, S. Grivet-Talocia, A. Quarteroni, G. Rozza, W.H.A. Schilders, L.M. Sileira (eds.). Model Order Reduction, Volume 2, Snapshot-Based Methods and Algorithms.. chapter of a book (pp. 245-307). De Gruyter .
    https://doi.org/10.1515/9783110671490-006.
  2. Smetana, K. (2020). Static Condensation Optimal Port/Interface Reduction and Error Estimation for Structural Health Monitoring. IUTAM Bookseries (vol. 36, pp. 1-24).
    https://doi.org/10.1007/978-3-030-21013-7_1.
Journal Article
  1. Smetana, K.; Zahm, O. (2020). Randomized residual-based error estimators for the proper generalized decomposition approximation of parametrized problems. International Journal for Numerical Methods in Engineering (23 ed., vol. 121, pp. 5153-5177).
    https://doi.org/10.1002/nme.6339.
  2. Smetana, K.; Zahm, O.; Patera, A. T. (2019). Randomized residual-based error estimators for parametrized equations. SIAM Journal on Scientific Computing (2 ed., vol. 41, pp. A900-A926).
    https://doi.org/10.1137/18M120364X.
  3. Brunken, J.; Smetana, K.; Urban, K. (2019). (Parametrized) first order transport equations: Realization of optimally stable Petrov-Galerkin methods. SIAM Journal on Scientific Computing (1 ed., vol. 41, pp. A592-A621).
    https://doi.org/10.1137/18M1176269.
  4. Buhr, A.; Smetana, K. (2018). Randomized local model order reduction. SIAM Journal on Scientific Computing (4 ed., vol. 40, pp. A2120-A2151).
    https://doi.org/10.1137/17M1138480.
  5. Smetana, K.; Ohlberger, M. (2017). Hierarchical model reduction of nonlinear partial differential equations based on the adaptive empirical projection method and reduced basis techniques. ESAIM: Mathematical Modelling and Numerical Analysis (2 ed., vol. 51, pp. 641-677).
    https://doi.org/10.1051/m2an/2016031.
  6. Smetana, K.; Patera, A. T. (2016). Optimal local approximation spaces for component-based static condensation procedures. SIAM Journal on Scientific Computing (5 ed., vol. 38, pp. A3318-A3356).
    https://doi.org/10.1137/15M1009603.
  7. Ohlberger, M.; Smetana, K. (2016). Approximation of skewed interfaces with tensor-based model reduction procedures: Application to the reduced basis hierarchical model reduction approach. Journal of Computational Physics (vol. 321, pp. 1185-1205).
    https://doi.org/10.1016/j.jcp.2016.06.021.
  8. Smetana, K. (2015). A new certication framework for the port reduced static condensation reduced basis element method. Computer Methods in Applied Mechanics and Engineering (vol. 283, pp. 352–383).
    https://doi.org/10.1016/j.cma.2014.09.020.
  9. Berninger, H.; Ohlberger, M.; Sander, O.; Smetana, K. (2014). Unsaturated subsurface flow with surface water and nonlinear in- and outflow conditions. Mathematical Models and Methods in Applied Sciences (5 ed., vol. 24, pp. 901-936).
    https://doi.org/10.1142/S0218202513500711.
  10. Ohlberger, M.; Smetana, K. (2014). A dimensional reduction approach based on the application of reduced basis methods in the framework of hierarchical model reduction. SIAM Journal on Scientific Computing (2 ed., vol. 36, pp. A714–A736).
    https://doi.org/10.1137/130939122.
Technical Report
    Courses

    MA 540: Introduction to Probability Theory