Fast, agile and efficient computing is my goal. My interest is to pursue the most advanced computational tools to empower society to solve today's urgent challenges.
Gabriel Wittum Professor, Applied Mathematics and Computational Sciences


  • Building 1, Office 0-117

Research Interests

  • Fast solvers for large systems of equations
  • Multiscale Numerics and Homogenization
  • Discretization
  • Inverse Modelling and Optimisation
  • Numerical methods for high dimensional problems
  • Numeric Geometry and Visualization
  • Computational Pharmacy
  • Computational Neuroscience
  • Mathematical Finance
  • Chemical and Process Engineering
  • Environmental Science
  • Computational Fluid Dynamics
  • Computational Electromagnetics
  • Structural Mechanics


Education Profile

  • Habilitation, University of Heidelberg, 1991
  • Ph.D. (Dr. rer.nat.) in Applied Mathematics, University of Karlsruhe, 1987
  • Diploma in Mathematics and Physics, Univerisity of Karlsruhe, 1983

Dr. Gabriel Wittum is Professor of Applied Mathematics and Computational Science and a member of the Extreme Computing Research Center.

Education and early career

He holds a Ph.D. in Applied Mathematics, at the University of Karlsruhe (1987) and a Postdoc at SFB 123, University of Heidelberg (1987 – 1991). Wittum’s scientific interests lie in developing software architectures, fast solvers for large systems of equations, multiscale numerics and homogenization, discretization, inverse modeling, and optimization enabling numerical methods for high dimensional problems. His work also focuses on numeric geometry and visualization. His research contributes to advance in Medicine and Neurosciences as well as Economics and Environmental Sciences.

Why modeling and simulations?

A general approach to modeling and simulation of problems from empirical sciences, in particular, using HPC. Foci are the development of advanced numerical methods for modeling and simulation in particular fast solvers like multigrid methods, allowing the application to complex realistic models, the development of corresponding simulation frameworks and tools, and the efficient use of top-level supercomputers for that purpose. These methods and tools are applied to problems from computational fluid dynamics, environmental research, energy research, finance, neuroscience, pharmaceutical technology and many more.


After 25 years as a professor at several universities in Germany, I was interested in a new challenge. KAUST’s vision as a hub for interdisciplinary research with a strong computational component convinced me to come to KAUST. As a computational and computer scientist, my home there is CEMSE.