Farabe Khan Alif is a statistician and academic specializing in applied and computational statistics. He completed his Master’s by Research at Universiti Putra Malaysia, where his work focused on extreme value theory, automated threshold selection for the Generalized Pareto Distribution, and applications to hydrological, financial, and public health datasets. His research has been presented at international conferences. He is currently a Lecturer in his early career at the University of Liberal Arts Bangladesh, teaching statistics- and mathematics-focused courses, while actively pursuing research in extreme value analysis, environmental statistics, and biostatistics.
Department of Business Administration
Bachelor of Business Administration (BBA)
Master of Business Administration (MBA)
Executive Master of Business Administration (EMBA)
MSc in Applied and Computation Statistics from Universiti Putra Malaysia (UPM), 2025.
BSc (With Honors) in Statistics from Jahangirnagar University, 2023.
Statistics, Extreme Value Statistics, Generalized Pareto Distribution, Generalized Extreme Value, Business Statistics, Environmental Statistics, Medical Statistica, Medical Extreme Value Application.
Current and Ongoing Research Projects
- Automated threshold selection methods for Peaks-Over-Threshold models with applications to hydrological and environmental datasets.
- Extreme value modeling of rainfall data addressing zero inflation and tail dependence through simulation-based approaches.
- Application of extreme value analysis to public health time series, including modeling dengue prevalence extremes and scenario-based risk estimation.
Completed Research Projects
- Automated Threshold Selection for the Generalized Pareto Distribution based on Goodness-of-Fit criteria (Master’s thesis, Universiti Putra Malaysia).
- Determinants of stunting and wasting among children in Bangladesh using DHS data (Undergraduate research project, Jahangirnagar University).
- Identifying learning styles of Bangladeshi university students using multivariate statistical methods (Factor Analysis).
Recent Conferences and Presentations
- Simposium Kebangsaan Sains Matematik ke-32 (SKSM32) 2025, Comparative Study of Threshold Selection Methods in Generalized Pareto Distribution with Application to Rainfall Datasets.
- 5th International Conference on Mathematical Sciences and Statistics (ICMSS) 2024, An Automated Threshold Selection Procedure for Generalized Pareto Distribution with Application to Rainfall Dataset.
Professional Awards and Honors
- Best Presenter Award, Simposium Kebangsaan Sains Matematik ke-32 (SKSM32), 2025.
- Special Graduate Research Allowance (SGRA), Universiti Putra Malaysia (2024).
- Special Graduate Research Allowance (SGRA), Universiti Putra Malaysia (2024–2025).
- Academic Merit-Based Scholarship, Jahangirnagar University (2018–2023).
- Alif, F. K., Ali, N., & Safari, A. (2025). An assessment on threshold selection for generalized Pareto distribution using goodness of fit. Malaysian Journal of Mathematical Sciences, 19, pp. 871–899.
- Alif, F. K., Ali, N., & Safari, A. (2025). An automated threshold selection procedure for generalized Pareto distribution with application to rainfall dataset. Mathematical Modeling and Computing, 12(3), pp. 819–831.
- Alif, F. K., Borna, M., Taslima, T., Hossain, M., & Salma, N. (2024). Identifying the learning style of university students in Bangladesh. Jahangirnagar University Journal of Science, Vol. 44 No. 1, pp.131-146.
- Farabe Khan Alif & Ali, N. (2025). Comparative Study of Threshold Selection Methods in Generalized Pareto Distribution with Application to Rainfall Datasets, Simposium Kebangsaan Sains Matematik ke-32 (SKSM32).
- Farabe Khan Alif, Ali, N., & Safari, A. (2024). An Automated Threshold Selection Procedure for Generalized Pareto Distribution with Application to Rainfall Dataset, 5th International Conference on Mathematical Sciences and Statistics (ICMSS).
- Orientation to ULAB
- Induction Training for Tertiary Teachers
- Teaching and learning strategies
- Student Advising
- Use of Technology (Moodle)
- Assessment of Learning