Kathrin Smetana (ksmetana)

Kathrin Smetana

Assistant Professor

Charles V. Schaefer, Jr. School of Engineering and Science

Department of Mathematical Sciences


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


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.

I am always looking for enthusiastic students and PostDocs with mutual research interests to join my group.

Prospective graduate students: Please, send me an email with your CV and a brief motivation letter and apply to the Pure and Applied Mathematics PhD program of the Stevens Institute of Technology. Currently, I am looking in particular for students interested in multiscale methods, model reduction, or randomized methods.

Prospective Postdocs: Please, send me an email with your CV including publication list, a brief motivation letter, and the names of two professors who could serve as a reference for you.


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)

Institutional Service

  • Research and Entrepreneurship Committee Member
  • Schaefer School of Engineering and Science Working Group on PhD Recruitment and Lab Culture Member
  • Co-Vice President of the Stevens Institute of Technology CAREER Club Chair
  • Research Computing Committee Member
  • Committee on Committees Member
  • SES Research Committee Member

Professional Service

  • Advances in Continuous and Discrete Models: Theory and Modern Applications: Member of Editorial Board
  • GEM - International Journal on Geomathematics: Guest Editor
  • National Science Foundation Review Panelist (Division of Mathematical Sciences)

Honors and Awards

NSF CAREER Award, 2022

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

  • AMS – American Mathematical Society. Member
  • SIAM – Society for Industrial and Applied Mathematics Member

Grants, Contracts and Funds

2023, NSF, "Conference: Mathematical Opportunities in Digital Twins (MATH-DT)"

2022, NSF, "CAREER: Randomized Multiscale Methods for Heterogeneous Nonlinear Partial Differential Equations", 6/1/2022-5/31/2027

2018, NWO, "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), 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 .
  2. Smetana, K. (2020). Static Condensation Optimal Port/Interface Reduction and Error Estimation for Structural Health Monitoring. IUTAM Bookseries (vol. 36, pp. 1-24).

Journal Article

  1. Smetana, K.; Taddei, T. (2023). Localized Model Reduction for Nonlinear Elliptic Partial Differential Equations: Localized Training, Partition of Unity, and Adaptive Enrichment. SIAM J. Sci. Comput. (3 ed., vol. 45, pp. A1300 - A1331).
  2. Schleuß, J.; Smetana, K.; Maat, L. t. (2023). Randomized quasi-optimal local approximation spaces in time. SIAM J. Sci. Comput. (3 ed., vol. 45, pp. A1066 - A1096).
  3. Hawkins, R.; Khalid, M. H.; Smetana, K. N.; Trampert, J. (2023). Model order reduction for seismic waveform modelling: inspiration from normal modes. Geophys. J. Int. (3 ed., vol. 234, pp. 2255–2283).
  4. Schleuß, J.; Smetana, K. (2022). Optimal local approximation spaces for parabolic problems. Multiscale Model. Simul. (1 ed., vol. 20, pp. 551–582).
  5. Brunken, J.; Smetana, K. (2022). Stable and efficient Petrov-Galerkin methods for a kinetic Fokker-Planck equation. SIAM Journal on Numerical Analysis (SINUM) (1 ed., vol. 60, pp. 157--179).
  6. 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).
  7. 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).
  8. 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).
  9. Buhr, A.; Smetana, K. (2018). Randomized local model order reduction. SIAM Journal on Scientific Computing (4 ed., vol. 40, pp. A2120-A2151).
  10. 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).
  11. 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).
  12. 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).
  13. 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).
  14. 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).
  15. 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).

Technical Report


    MA 540: Introduction to Probability Theory
    MA 346: Numerical Methods
    MA 615: Numerical Analysis
    MA 653: Numerical Solutions of Partial Differential Equations