It might sound straightforward, but the two most important things for success in research are interest and a good and solid education.

Education and early career

  • Doctor rerum naturalium (with distinction, “summa cum laude”) in Mathematics, The Free University of Berlin (FU Berlin), Germany (2001)
  • Diploma in Mathematics, FU Berlin, Germany (1996)
  • Rhetoric and Communication Training: Friedrich–Naumann Foundation, Bonn, Germany (1991)
  • Study of Mathematics, FU Berlin, Germany; Minor field of study: Economics (1990-1996)
  • Abitur/Matura, Evangelisches Gymnasiums zum Grauen Kloster zu Berlin, Germany (1990).

Institutional responsibilities and academic service 

  • July 2007 to March 2009: Chairman of the examination board for the new Bachelor’s and Master’s Studies in Mathematics at the University of Bonn (UOB), Germany.
  • July 2007 to March 2009: Chairman of the board of finance for tuition fees in Mathematics, UOB.
  • 2009–2013: Director, master specialization “Applied Mathematics and Computational Science,” Università della Svizzera italiana, Italy (USI).
  • 2009–2020: Director of the Institute of Computational Science, USI.
  • 2013–2015: Vice-Director of the master program “Computational Science,” USI. 
  • Since 2014: Co-Director of the Center for Computational Medicine in Cardiology, USI.
  • 2017–2021: Member of the academic senate of USI (two election periods).
  • Since 2021: Director of the interdisciplinary faculty at the Euler Institute, USI.
  • 2022: (Founding) Dean of the Faculty of Mathematics and Informatics at UniDistance Switzerland.

Areas of expertise and current scientific interests

Applied mathematics, computational mechanics, contact problems in mechanics, scientific software, multilevel and domain decomposition methods, optimization, iterative solution of large-scale systems, parallel computing, high-performance computing (HPC), coupled problems, finite elements, non-linear solution methods, neural networks, physics-informed neural networks, cardiac simulation, biomechanics and computational geoscience.

Application areas

  • Medicine 
  • Computational mechanics 
  • Contact problems 
  • Fluid-structure interaction 
  • Cardiac simulation 
  • Biomechanics
  • Geology 
  • Complex and coupled multiphysics.

Editorial activities

  • Numerische Mathematik.
  • Former Associate Editor of the SIAM Journal on Scientific Computing (SISC).
  • Career recognitions
  • MATH+ Distinguished Visiting Scholar, MATH+ Center, Berlin, Germany (2020).
  • Award for Ph.D. (Doctor rerum naturalium with distinction (“summa cum laude”)), FU Berlin, Germany (2001).
  • Membership of the High-Q Club, Forschungszentrum Jülich Research Center, Germany (2013).
  • Offer for a full W3 professorship “Wissenschaftliches Rechnen,” (Scientific Computing), University of Hannover, Germany (2014).
  • Offer for a full W3 professorship in Scientific Computing at the University of Mainz, Germany (2008).
  • Youngest professor at the University of Bonn, Germany, at the start of duty in 2003.
  • Taylor & Francis Prize for “Innovative Contribution to Theoretical Biomechanics/Biomedical Engineering” (2008).
  • Zuse Institute Berlin Fellowship (2004).
  • Best Poster Award at the Computer Science & Mathematics, Platform for Advanced Scientific Computing (PASC) 14.
  • Best Poster Award, PASC 15.
  • Best Poster Award, PASC 16.
  • Best Poster Award at the 12th IEEE Engineering in Medicine and Biology Society (1990); 
  • Best Poster at the Swiss Competence Center for Energy Research-Supply of Electricity Conference (2019).

Research achievements

A comprehensive list of Dr. Krause’s research achievements. 


“KAUST is an excellent environment for research (people and infrastructure). The working conditions are attractive. The University is also part of a larger vision and strategy built on research and innovation. Being a part of such an active environment is also stimulating.”

Research Interests

  • Numerical solution of partial differential equations
  • Finite elements 
  • Fast solution methods for large-scale problems 
  • HPC (high-performance computing) 
  • Multigrid and domain decomposition
  • Optimization
  • Machine Learning.