Dr. Dhafer Malouche is a Professor of Statistics at Qatar University, with more than 25 years of academic experience across Europe, North Africa, the Middle East, and North America. He earned his Ph.D. in Statistics and Applied Mathematics from Paul Sabatier University and has held faculty positions in Tunisia, Egypt, and Qatar.

His international experience includes appointments as a Fulbright Scholar at Stanford University (2011) and the University of Michigan (2016–2017), as well as long-term research collaborations with Yale University through the MacMillan Center (2014–2019). His work during these periods addressed survey methodology, data quality, governance, and applied statistical modeling in social and health sciences.

Dr. Malouche’s current research focuses on advanced statistical modeling for population health, with particular emphasis on Bayesian networks, graphical models, epidemiological modeling, and reproducible data science. He is actively involved in large-scale biomedical research using data from the Qatar Biobank and primary healthcare systems, leading and co-authoring studies on chronic pain, cardiometabolic risk, autoimmune diseases, respiratory health, and mental health indicators. His recent work also examines the reliability of AI-detection tools in scientific publishing and the integration of reproducible statistical workflows in medical research.

In teaching, Dr. Malouche delivers advanced courses at both undergraduate and doctoral levels, including stochastic processes, actuarial statistics, and advanced biostatistics for PhD students in the biological sciences. He makes extensive use of R, Bayesian methods, and real-world health data, and regularly develops reproducible teaching materials, Shiny applications, and LaTeX-based resources to support applied statistical training.

Beyond academia, Dr. Malouche has served as a statistical consultant for international organizations, including the World Health Organization, contributing to analyses of COVID-19 impacts on mental health and health systems. At Qatar University, he continues to lead interdisciplinary research, supervise graduate students, and contribute to methodological innovation at the intersection of statistics, public health, and data science.

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