Mohamed Megheib holds a Ph.D. and a Master's degree in Statistics from George Washington University (GWU), USA. He has taught various statistics courses at George Washington University and Georgetown University. During his teaching and consultant roles at GWU, he received five merit awards. Dr. Megheib worked as a postdoctoral fellow at the Institute for Modeling Collaboration and Innovation (IMCI), where he participated in four projects: COVID-19, small area estimation, genomic analysis, and geno-to-pheno. He also served as a senior stat scientist at the FDA, where he provided statistical guidance in the decision process for marketing approval of therapeutic drugs for hematology indications. Furthermore, Dr. Megheib has worked as a senior statistician at international and local organizations such as SAS, Arriyadh Development Authority (ADA), Intelliknowledg, and World Population Council. He is proficient in a wide range of approaches, including regression, time-series analysis, and social network analysis. He specializes in supporting multiple methods using various software, including SQL, Python, R, SAS, STATA, and SPSS.Dr. Megheib's research areas include parametric and nonparametric modeling, biostatistics, modeling of correlated data, spatial statistics, composite indicators, key performance indicators, survey research, model comparison, misspecification, Bayesian inference, econometrics, and applications of statistics in social sciences, as well as small area estimation.