Biography

Mohammed Thajeel Abdullah have a Master's in Information Technology from the University of Utara Malaysia and PhD in computer science from Informatics Institute for Postgraduate Studies, Iraqi. He has taught undergraduate courses at Al-Furat Al-Awsat Technical University - Kerbala Technical Institute, Iraq. He is currently a lecturer at the same institute. His research interests include the use of artificial intelligence methods and the Analysis and design of Data warehouses with information systems. Personal email: - [email protected] Phone number: - 07730535157

Books

  • Data warehouse model for monitoring key performance indicators (KPIs): A Requirement Goal Analysis for Data Warehouse KPI (ReGADaK) approach

Rsearch Interests

  • Artificial Intelligence Technologies
  • Deep Learning
  • Machine Learning
  • DeepFake
  • Image Processing
  • Analysis and design of Data warehouses with information systems.

Experiences

  • • Holds an international certificate of computers and the Internet (IC3).
  • • Holds an international certificate of ( English language Plocement lest (EIPT)).

Positions

  • Coordinator of Computer Systems in Al-Furat Al-Awsat Technical University/Technical Institute of Karbala (2011-2013).
  • Lecturer in Al-Furat Al-Awsat Technical University/Technical Institute of Karbala from 2006 to Present.
  • Manager of the division students’ affairs in Al-Furat Al-Awsat Technical University/Technical Institute of Karbala from 2017 to Present.
  • Head of Networks and Software Computer Department in Technical Institute of Karbala from 2024 to Present.

Scientific Research

  • Data warehouse model for monitoring key performance indicators (KPIs) using goal-oriented approach https://doi.org/10.1063/1.4960940
  • Machine learning algorithms for distributed operations in internet of things IoT http://pen.ius.edu.ba/index.php/pen/article/view/879
  • Convolutional Neural Networks Based Optimal Management of Agricultural Crops https://doi.org/10.17762/turcomat.v12i11.5890
  • Increase the Accuracy of Detection of Pathogenic Genes of Breast Cancer using a Graph-Based Approach to the Gene Prioritization Problem https://doi.org/10.31185/wjps.185
  • DeepFake Detection Improvement for Images Based on a Proposed Method for Local Binary Pattern of the Multiple-Channel Color Space DOI: 10.22266/ijies2023.0630.07
  • Deploying Facial Segmentation Landmarks for Deepfake Detection https://doi.org/10.1063/5.0213294
  • Facial deepfake performance evaluation based on three detection tools: MTCNN, Dlib, and MediaPipe https://doi.org/10.1063/5.0213294

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