Dr. Mohamed Kamel Riahi
Dr. Mohamed Kamel Riahi Assistant Professor
Technical Areas
Research Interests

Assistant Professor, Department of Mathematics

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.

  • Ph.D in Mathematical Sciences
  • MS.c In Applied Mathematics
Technical Areas
  • MATH 111-MATH212 Calculus
  • MATH315 Advanced Linear Algebra
  • MATH 412 Optimization
  • MATH602 Advanced Numerical Methods (Master degree)
  • MATH319-MATH419 Numerical Analysis and Scientific computing
  • MATH316 Partial differential equations
Research Interests
  • A/ Partial Diffirenial Equations:(Finite element methods. Finite difference methods. Integral equations. Numerical
    Analysis. Non-linear Optimization.)
  • B/ Mathematical Physics/Engineering: Reaction diffusion systems. Wave propagation. Electromagnetism. Fluid mechanics,
    Heat transfer, NMR.
  • C/ Robust Solvers: Domain decomposition method, Parareal method. High performance computing and parallel programming.
    D/ 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.
  • High performance Computing and Parallel programming.
    Numerical solution for PDEs.