Regular biography
Taban Baghfalaki is a Lecturer in Statistics at The University of Manchester, Department of Mathematics. Their research focuses on statistical methodology with applications in areas such as Bayesian statistics, joint modeling, missing data analysis, high-dimensional data, big medical data analysis, and dynamic risk prediction. They are currently accepting PhD students and are involved in projects related to statistical methodology for dynamic risk prediction in extreme clinical cases. They also supervise Master’s dissertations and teach Bayesian Statistics at the undergraduate and Master’s levels.
Scholar-generated biography
Taban Baghfalaki is a Lecturer in Statistics at the University of Manchester, specializing in longitudinal data analysis, joint modeling, Bayesian analysis, and variable selection. Their research focuses on integrating longitudinal measurements with time-to-event data using Bayesian methods, particularly in robust and flexible modeling frameworks. Baghfalaki's work addresses challenges such as misclassification, censoring, and non-ignorable missingness in health and social sciences data. They have applied these methods to diverse areas including road traffic injuries, maternal smoking, and breast cancer risk assessment. Their publications highlight the use of copula approaches, quantile regression, and mixed ordinal-continuous longitudinal models to improve statistical inference in complex datasets.