Overview

Achraf Cohen is an Associate Professor of Statistics and Data Science. Dr. Cohen teaches Statistics and Data Science courses to graduate and undergraduate students.

Short description of your current research project:

Dr. Cohen’s research focuses on statistical process monitoring (SPM). In the context of his work, SPM refers to the statistical techniques, tools, and practices that improve system monitoring, anomaly detection, and statistical control charts. One of the best ways to develop a monitoring system is to combine the three schools of thought in the literature, which are (1) statistical approach (a.k.a. SPM), which is concerned with collecting data from processes to develop statistical monitoring models, (2) knowledge-based approach that is based on experts’ knowledge and their expertise, and (3) model-based approach that requires a prior physical and mathematical description of the process. Any description (data, expert, and physical/mathematical knowledge) of the process provides new information and reinforces system understanding. In particular, my research focuses on statistical models for process monitoring.

In addition to SPM, his research interests are in the intersection of statistical modeling and machine learning (inferences and predictive models), anomaly detection, wavelets analysis, and applied machine learning. His contributions span various domains, including education analytics, quality engineering, sports medicine, and IoT systems, emphasizing the versatile applications of data science.