Dr. Mohamed Kamel Riahi
Dr. Mohamed Kamel Riahi Assistant Professor Mathematics

Contact Information
mohamed.riahi@ku.ac.ae +971 2 312 3563


Dr. Mohamed K. Riahi earned his PhD in Applied Mathematics from Pierre et Marie Curie University, Paris, France. He has worked as a postdoc research associate in the Department of Mathematical Sciences at New Jersey Institute of Technology, USA, and in INRIA-Saclay Palaiseau France as a postdoc researcher, with DeFI Team.

Dr. Riahi is an expert in scientific computing and numerical analysis related to partial differential equations. His research includes and is not limited to: space- time-domain decomposition methods, finite element method, integral equations method, numerical optimization, iterative method, preconditioning technique, shape optimization, optimal control problem, high-performance computing, and parallel programming.

He applies his research on waves related problems (acoustics and electromagnetism), fluid-structure interaction, heat and mass transfer, and inverse problems.

Dr. Riahi is serving as referee for several peer-reviewed applied mathematical journals.

  • PhD in Mathematical Sciences
  • MSc In Applied Mathematics

  • Calculus
  • Advanced Linear Algebra
  • Optimization
  • Advanced Numerical Methods (Master's degree)
  • Numerical Analysis and Scientific computing
  • Partial Differential Equations

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Affiliated Centers, Groups & Labs

Research Interests
  • Partial differential equations
    • Finite element methods
    • Finite difference methods
    • Integral equations
    • Numerical analysis
    • Non-linear optimization
  • Mathematical physics/engineering
    • Reaction diffusion systems
    • Wave propagation
    • Electromagnetism
    • Fluid mechanics
    • Heat transfer
    • NMR
  • Robust solvers
    • Domain decomposition method
    • Parareal method
    • High-performance computing and parallel programming
  • Inverse problems
    • Optimal control
    • Shape optimization
    • Parameters identification
  • Numerical analysis and scientific computing inverse problems
  • Optimization and optimal control theory
  • Computational fluid mechanics
  • Computational physics
  • Computational electromagnetism
  • Numerical solution for PDEs.