Dr. Fouad Khalawi | Mathematics | Best Researcher Award
Assistant Professor at King Abdulaziz University, Saudi Arabia
Dr. Fouad Ali Hussein Khalawi is a dedicated academic in Applied Statistics, currently serving as an Assistant Professor at King Abdulaziz University. With a career marked by analytical depth and interdisciplinary reach, he brings over 17 years of teaching and research experience. His work is centered on developing innovative statistical methodologies and applying them to real-world problems, particularly in experimental design, lifetime data analysis, and agricultural studies.
Profile
Education
Dr. Khalawi began his academic journey with a B.Sc. in Statistics from King Abdulaziz University in 2007, where his project explored the Central Limit Theorem through simulation studies. He continued at the same institution to earn his M.Sc. in Mathematical Statistics in 2012, focusing his thesis on statistical inference for lifetime distributions with varying failure rate types. In 2022, he completed his Ph.D. in Applied Statistics at North Dakota State University, where his research led to the development of novel nonparametric tests tailored for location and scale testing in mixed designs.
Experience
Dr. Khalawi’s academic career is rooted in long-standing service to King Abdulaziz University. He began as a Teaching Assistant in 2007, advanced to Lecturer in 2014, and has held the position of Assistant Professor since 2022. His teaching portfolio spans core statistical theory and applied data analysis, delivered with expertise in tools like SAS, SPSS, MINITAB, and Python. Beyond classroom instruction, he actively mentors students and contributes to curriculum development, fostering a hands-on learning approach grounded in statistical rigor.
Research Interests
Dr. Khalawi’s research focuses on nonparametric testing procedures, statistical modeling in mixed experimental designs, and lifetime data analysis. His doctoral work introduced pioneering test statistics under the simple tree alternative, offering greater flexibility and efficiency in analyzing real-world data. Additionally, he is deeply involved in interdisciplinary research, including fatigue modeling in materials science and agricultural field data analysis, especially in plant pathology—areas where his statistical innovations have wide-reaching applications.
Awards
Dr. Khalawi’s academic promotions and publication record reflect recognition of his expertise and impact. His advancement through academic ranks and collaboration in high-impact research signal peer acknowledgment of his scholarly contributions.
Publications
Dr. Khalawi has authored several peer-reviewed papers in reputable journals, contributing to both theoretical statistics and applied methodologies:
- “Proposed nonparametric tests for the simple tree alternative for location and scale testing in a mixed design,” International Journal of Engineering Science Invention (2022) – cited in experimental design analyses.
- “Location and scale testing in mixed design,” International Journal of Statistics and Applied Mathematics (2023) – referenced in methodological developments in statistical inference.
- “Modeling Fatigue Data of Complex Metallic Alloys Using a Generalized Student’s t-Birnbaum-Saunders Family of Lifetime Models,” Crystals (2025) – cited in engineering and materials science studies. These works have gained scholarly citations and further extended the practical scope of statistical tools across disciplines.
Conclusion
Dr. Khalawi exemplifies the role of a modern statistician—equally grounded in theory and oriented toward practical application. His career reflects a consistent drive to improve statistical inference methods and apply them to interdisciplinary challenges. As a researcher, educator, and contributor to public knowledge, his efforts advance both academic excellence and impactful innovation, making him an exemplary candidate for academic recognition.