Name

Lecturer:Kadhem Al-Daffaie

Personal Overview

Kadhem Al-Daffaie received his BSc and MSc Degrees in Statistics from Baghdad University, Iraq in 2008 and 2011, respectively. In 2019, he received his PhD degree in Statistics from the University of Southern Queensland, Australia. He is a lecturer at Al-Muthanna University, Iraq since 2011. His research interests involve: applied statistics, human gait analysis, statistical techniques for human gait analysis, machine learning methods for forecasting & classification purposes in various fields.

Educational Background

Ph.D:PhD degree in Statistics from the University of Southern Queensland, Australia

M.Sc:BSc and MSc Degrees in Statistics from Baghdad University, Iraq

B.Sc:BSc and MSc Degrees in Statistics from Baghdad University, Iraq

Contact Information

Email:kadhem.aldaffaie@mu.edu.iq

Phone:+9647827222750

Selected Publications

AL‐Musaylh, Mohanad S., Kadhem Al‐Daffaie, and Ramendra Prasad. “Gas consumption demand forecasting with empirical wavelet transform based machine learning model: A case study.” International Journal of Energy Research (2021).
Al-Daffaie, Kadhem, and Albert K. Chong. “Advanced techniques to study foot pressure of healthy young adults.” Proceedings of the 2019 2nd International Conference on Information Science and Systems. 2019.
Al-Daffaie, Kadhem, and Shahjahan Khan. “Logistic regression for circular data.” AIP Conference Proceedings. Vol. 1842. No. 1. AIP Publishing LLC, 2017.
Al-Daffaie, Kadhem, and Hadi Ratham Al-Ghayab. “TRANSIENT ARTIFACT REDUCTION AND STATISTICAL METHOD BASED CLASSIFICATION OF NEURODEGENERATIVE DISEASES.” Int. J. Agricult. Stat. Sci. Vol 16.1 (2020): 1391-1399.
Al-Daffaie, Kadhem, Albert K. Chong, and Zahra Gharineiat. “Pressure beneath the foot for older adults using an improved approach.” 2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE). IEEE, 2019

Research Interests

Applied Statistics, Human Gait Analysis, Machine Learning, Deep Learning, Forecasting, Classification

Research Links

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