Saddam Hussain
Date and institution of PhD awarded:
May 11, 2022, Universiti Teknologi Malaysia (UTM)
Further academic qualifications:
2018-2022: PhD specializing in Applied Machine Learning/Data Science, Universiti Teknologi Malaysia (UTM); Thesis: “Intelligent Feature Engineered-Machine Learning-Based Electricity Theft Detection Framework for Labeled and Unlabeled Datasets”
2008-2013: Master of Engineering (MEng) in Electrical Engineering, Mehran University of Engineering and Technology, Pakistan
2008-2013: Master of Engineering (MEng) in Electrical Engineering, Mehran University of Engineering and Technology, Pakistan
Specialisation:
Data Scientist | Expert in Advanced Mathematics, Statistics, and Algorithms | Academic Researcher | Business Analyst | AWS Data Analyst Professional | Delivering End-to-End Data Science Solutions
Department/Section:
ORCID:
Participation in scholarly communities and networks:
Contact:
Participation in grants:
- Postdoctoral Researcher in the project “Imperial Commoners in Brazil and West Africa (1640–1822): A Global History from a Correspondence Network Perspective” on behalf of the National Science Center (Project No. 2022/45/B/HS3/00473) under the direction of Dr. Agata Błoch.
- [with M. W. Mustafa, S. E. James & S. K. Baloch] “ Electric Theft Detection Using Unsupervised Machine Learning-Based Matrix Profile and K-Means Clustering Technique” Computational Intelligence in Machine Learning: Select Proceedings of ICCIML 2021. Singapore: Springer Nature Singapore, 2022, pp. 15-24.
- [with Z. H. Leghari, A. Memon, A. H. Memon, & A. A. Baloch] “Parameter‐Free Improved Best‐Worst Optimizers and Their Application for Simultaneous Distributed Generation and Shunt Capacitors Allocation in Distribution Networks”. International Transactions on Electrical Energy Systems, 1 (2022), p. 6833488.
- [with O. O. Mohammed, M. W. Mustafa, S. Salisu, A. Memon, S. Hussain, A. O. Otuoze, O. Ibrahim] “Assessment of the influence of wind energy incorporated capacity benefit margin in ATC computation.” International Journal of Applied 11.2 (2022), pp. 145-155.
- [with Wazir Mustafa Mohd, Touqeer A. Jumani, Shadi Khan Baloch, Hammad Alotaibi, Ilyas Khan, Afrasyab Khan] “A novel feature engineered-CatBoost-based supervised machine learning framework for electricity theft detection”. Energy Reports, 7 (2021), pp. 4425-4436.
- [with M. W. Mustafa, K. H. A. Al-Shqeerat, F. Saeed, & B. A. S. Al-Rimy] “A novel feature-engineered–NGBoost machine-learning framework for fraud detection in electric power consumption data”. Sensors, 24 (2021), p. 8423.
- [with M. W. Mustafa, T. A. Jumani, S. K. Baloch, & M. S. Saeed] “A novel unsupervised feature‐based approach for electricity theft detection using robust PCA and outlier removal clustering algorithm”. International Transactions on Electrical Energy Systems, 30(11) (2020), p. 12572.
