• Kristina Steih
  • Helmholtzstr. 20
  • Room 1.62
  • 89081 Ulm
  • Phone: +49 731 50 31705          
  • Postal Address:
  • Institute for Numerical Mathematics
  • Ulm University
  • 89069 Ulm

Research Interests

Reduced Basis Methods (RBM)

Reduced Basis Methods are a model reduction tool for parameterized partial differential equations.


  • RBM for time-periodic problems
  • RBM for space-time formulations
  • RBM with adaptive offline computations
  • RBM using wavelets
  • (Time-dependent) parameter functions
  • Parameter dependent domains
  • Development of rigorous a posteriori error bounds for time-periodic problems

Time-Periodic PDEs

  • Space-time formulations
  • Existence and uniqueness
  • Numerical Solvers: Fixed-point methods, space-time approaches


Conferences, Workshops and selected Talks


since 09/2011

Research Assistant in the Institute for Numerical Mathematics, Ulm University

09/2008 - 09/2011

PhD Student in the DFG Research Training Group 1100, Ulm University


Research visit with Prof. Dr. Anthony T. Patera, Department for Mechanical Engineering, MIT, USA

10/2002 - 09/2008

Studies of Mathematics and Economics, Ulm University, Degree: Dipl. math. oec.
Diploma Thesis: "Solving Markov Decision Processes by Simulation: a Model-Based Approach"

09/2006 - 06/2007

Study visit (Erasmus) at the Faculté d'Economie appliquée, Université Paul Cézanne, Aix-en-Provence


SS 14

Exercises Numerical Finance
Exercises Programming (with C++, for CSE students)

WS 13/14

Exercises WiMa Praktikum 2
Seminar Modell reduction of linear systems

SS 13

Exercises High Performance Computing
Exercises Programming (with C++, for CSE students)

WS 12/13

Exercises Numerical Finance

SS 12

Exercises Numerics of partial differential equations 2
Exercises Programming (with C++, for CSE students)

WS 11/12

Exercises Numerical Mathematics I

SS 09

Reading Course Numerical Finance

SS 08

Exercises Introduction to Operations Research
(Institute for Optimization and Operations Research)

WS 07/08

Exercises Operations Research I
(Institute for Optimization and Operations Research)