Dr. Achraf Cohen

  • Position:  Post-Doctoral Teaching Associate
  • Department:  Mathematics and Statistics
  • Office Location:  Building 4, Room 333
  • Campus: (850) 474-3440


Dr. Achraf Cohen is a Post-Doctoral Associate here at UWF. Dr. Cohen has a Ph.D. in Applied Mathematics-Statistics from University of Angers (France).  He received his M.S. in Telecoms Engineering from the National School of Applied Sciences in Morocco. His research concerns statistical process control and wavelets analysis.

He has shown that using wavelets coefficients in order to design new control charts can be an additional and efficient tool for process control. He is currently teaching Multivariate Methods, and he has taught Nonparametric Statistics and Statistical Process Control in the past. Dr. Cohen's special interests lies in Data-Driven techniques for process monitoring, statistics of wavelets coefficients, control charts and statistical process control.

Degrees & Institutions:

Ph.D. in Applied Mathematics-Statistics, University of Angers, France
M.S. in Telecommunication Engineering , ENSAT School Engineering, Morocco


My research interests concern data-driven process monitoring, statistical process control and wavelets analysis.

Current Courses:

  • Multivariate Methods

Classes Taught:

    • Nonparametric Statistics
    • Statistical Process Control

Special Interests:

Data-driven approaches for process monitoring, Statistical Quality Control, Wavelets Analysis.


    A. Cohen, R. Amin. The Effects of Normal Mixtures and Autocorrelation on the Fraction Non-Conforming. Communications in Statistics - Simulation and Computation, In Press.

    A. Cohen, T. Tiplica, A. Kobi. OWave control chart for monitoring the process mean. Control Engineering Practice, Vol. 54, pp. 223-230. 2016.

    A. Cohen, T. Tiplica, A. Kobi. Design of experiments and statistical process control using wavelets analysis. Control Engineering Practice, Vol. 49, pp. 129-138. 2016.

Keywords: Statistical process control, wavelets analysis, the statistics of wavelets coefficients, data-driven process monitoring, data analysis