Raid Luaibi Lafta

About

Assistant Dean for Scientific Affairs of the College of Engineering, University of Shatrah, since 1 September 2026; Head of the Department of Computer Engineering and Artificial Intelligence from 6 October 2023 to 1 September 2026, and Head of the Studies and Planning Department from 2019 to 2023. He holds a B.Sc. in Computer Science from the University of Thi-Qar (2002), an M.Sc. in Information Technology from Voronezh State University, Russia (2010), and a Ph.D. from the Faculty of Health, Engineering and Sciences, University of Southern Queensland, Australia. His research covers predictive data mining of medical time series, intelligent recommender systems for patients with chronic diseases in telehealth environments, and EEG signal analysis. He has more than 10 papers, including papers in Q1 journals, and has presented at more than 5 international conferences in Germany, Singapore, South Korea, Australia and Japan.

Publications (16)

1. 1. Coupling a dual tree - complex wavelet transform with K-means to clustering the epileptic seizures in EEG signals — 2025
2. 2. Unmasking Fake News: A Naïve Bayes Classifier Approach to Combat Misinformation — 2025
3. 3. Classification of epileptic based on fast Fourier transform and ensemble model — 2024
4. 4. EEG and Fractal Dimension for Epileptic Seizures Detection — 2023
5. 5. Fast Fourier Transform and Ensemble Model to Classify Epileptic EEG Signals — 2022
6. 6. Clustering similar time series data for the prediction the patients with heart disease — 2022
7. 7. Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm — 2019
8. 8. A general extensible learning approach for multi-disease recommendations in a telehealth environment — 2018
9. 9. A Structural Graph-Coupled Advanced Machine Learning Ensemble Model for Disease Risk Prediction in a Telehealthcare Environment — 2018
10. 10. A Recommender System with Advanced Time Series Medical Data Analysis for Diabetes Patients in a Telehealth Environment — 2018
11. 11. A Fast Fourier Transform-Coupled Machine Learning-Based Ensemble Model for Disease Risk Prediction Using a Real-Life Dataset — 2017
12. 12. Coupling a Fast Fourier Transformation With a Machine Learning Ensemble Model to Support Recommendations for Heart Disease Patients in a Telehealth Environment — 2017
13. 13. An intelligent recommender system based on predictive analysis in telehealthcare environment — 2016
14. 14. Adopting Hybrid Descriptors to Recognise Leaf Images for Automatic Plant Specie Identification — 2016
15. 15. IRS-HD: An Intelligent Personalized Recommender System for Heart Disease Patients in a Telehealth Environment — 2016
16. 16. An Intelligent Recommender System Based on Short-Term Risk Prediction for Heart Disease Patients — 2015