Accepting applications from PhD students.
Jamal is a Lecturer in Applied Health Statistics at the School of Health Sciences, University of Southampton. He completed both his B.Sc. (Hons) and Masters in Statistics with distinction, acquiring a strong foundation in quantitative methods and health survey data analysis. Later, he pursued a PhD in Social Statistics & Demography at the University of Southampton, UK, funded by the prestigious Commonwealth Scholarship and Grants. His doctoral research focused on developing novel statistical estimation and inference methods for analysing Demographic and Health Survey spatial geo-masking data, preserving respondent confidentiality and data integrity.
With a passion for quantitative research methods and health survey spatial data analysis, Jamal is a confident user of the menu-driven (SPSS, Stata) and programme-based (e.g., R) statistical packages. He specializes in multilevel modelling and longitudinal data analysis, applying these techniques to advance medical and social science research. Jamal's proficiency in statistical and machine learning methods has led to the application of these techniques in healthcare and social science, contributing to improved data-driven decision-making processes.
Prior to his current position, Jamal served in various roles, including as a Post-Graduate Teaching Assistant (PGTA), Research Fellow, and Lecturer/Assistant Professor in Applied Statistics at universities in the UK and abroad. He has taught courses such as Quantitative Research Methods, Applied Regression Analysis, Generalised Linear Models, and Analysis of Multilevel & Longitudinal Data to both undergraduate and postgraduate students from diverse backgrounds.
With a focus on interdisciplinary research, Jamal continues to explore innovative approaches in statistical analysis, ensuring that his work contributes significantly to the fields of Applied Health Statistics and beyond.