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 research spans a broad range of statistical and interdisciplinary domains. In biomedical and public health research, he works extensively with Qatar Biobank data, leading and co-authoring studies on chronic pain, cardiometabolic risk, autoimmune diseases, hematological abnormalities, and gender disparities in quality of life. His clinical collaborations extend to oncology (pancreatic cancer, T-cell leukemia), neurological disorders (multiple sclerosis), and systematic reviews of clinical outcomes. His methodological contributions focus on Bayesian networks, graphical models, epidemiological modeling, and reproducible data science workflows. Beyond biomedical research, he collaborates on engineering education and educational technology, examining the impact of virtual reality and blended learning on student engagement. He is also engaged in interdisciplinary work at the intersection of statistics, AI regulation, anticipatory law, and finance, applying quantitative foresight methods to emerging legal and economic challenges. His recent work further examines the reliability of AI-detection tools in scientific publishing.

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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