Dr. Mohamed Kamel Riahi
Dr. Mohamed Kamel Riahi Assistant Professor
Teaching 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.

  • PhD in Mathematical Sciences
  • MSc In Applied Mathematics
Teaching Areas
  • Calculus
  • Advanced Linear Algebra
  • Optimization
  • Advanced Numerical Methods (Master's degree)
  • Numerical Analysis and Scientific computing
  • Partial Differential Equations
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.