Ahlam Khaled Mohammed Al-Dhamari

 

Dr. Ahlam Khaled Mohammed Al-Dhamari

Ph.D , MSc, BEng (Hons)
Department of Electrical and Computer Engineering 
Lecturer

Contact Details
Location: Skylark 3 Room 456
Tel: +60 85 630100 Ext: 2449
Fax: +60 85 630288
Email: ahlam.aldhamari@curtin.edu.my

Google Scholar: https://scholar.google.com/citations?user=P0yClUoAAAAJ&hl=en
ResearchGate: https://www.researchgate.net/profile/Ahlam-Al-Dhamari
SCOPUS: https://www.scopus.com/authid/detail.uri?authorId=57193843458
ORCID: https://orcid.org/0000-0001-7595-4632 
Web of Science: https://www.webofscience.com/wos/author/record/HJH-1739-2023
LinkedIn: https://www.linkedin.com/in/ahlam-al-dhamari-a0a96160/

Background

Ahlam Al-Dhamari received her PhD in Electrical Engineering (Computer Engineering) from Universiti Teknologi Malaysia (UTM), MSc in Computer Engineering and Networks from University of Jordan, and BEng in Computer Science and Engineering from Hodeidah University. Her research interests include Artificial Intelligence, Computer Vision, Machine Learning, Deep Learning, Image and Video Processing, Abnormal Detection, and Motion Analysis. She is a member of ACM, IEEE and MBOT. Ahlam began her teaching career in 2008 as an assistant lecturer at Hodeidah University (2008-2012). She subsequently served as a postdoctoral fellow under an international fellowship scheme at UTM (2021-2023). In April 2024, she joined Curtin University Malaysia as a lecturer in the Electrical and Computer Engineering Department.

Academic History

  • PhD in Electrical Engineering (Computer Engineering), Universiti Teknologi Malaysia (UTM), 2020
  • Master’s degree in Computer Engineering and Networks, University of Jordan, 2015
  • Bachelor’s degree in Computer Science and Engineering (First Class Honours), Hodeidah University, 2008

Research Interest

  • Artificial Intelligence
  • Computer Vision
  • Machine Learning
  • Deep Learning
  • Image and Video Processing
  • Motion Analysis
  • Crowd Analysis and Management
  • Natural Language Processing
  • Computer Security
  • Expert in MATLAB, PYTHON, C/C++ and JAVA programming languages

Awards

  • Post-Doctoral Fellowship, Universiti Teknologi Malaysia (2021-2023)
  • PhD Fellowship award, Hodeidah University (2016-2020)
  • MSc Scholarship award, German Academic Exchange Service (DAAD) (2012-2015)

Publications

A. Journal Publication

  1. Hafeezallah, A., Al-Dhamari, A.*, and Abu-Bakar, S. A. R. (2024). Motion Segmentation Using Ward’s Hierarchical Agglomerative Clustering for Crowd Disaster Risk Mitigation. International Journal of Disaster Risk Reduction.
  2. Mohammed, M. S., Al-Dhamari, A.*, Abdul-Qawy, A. S. H., Abdul-Malik HY Saad, Hamdan, M, and Marsono, M. N. (2023). 3D-DTaPO: Dynamic Thermal-Aware Performance Optimization for 3D Dark silicon Many-core Systems. IEEE Access.
  3. Mohammed, M. S., Al-Dhamari, A.*, Saeed, W., AL-Aswadi, F. N., Saleh, S. A. M., and Marsono, M. N. (2023). Motion Pattern-Based Scene Classification Using Adaptive Synthetic Oversampling and Fully Connected Deep Neural Network. IEEE Access.
  4. Hafeezallah, A., Al-Dhamari, A.*, and Abu-Bakar, S. A. R. (2023). Visual Motion Segmentation in Crowd Videos Based on Spatial-Angular Stacked Sparse Autoencoders. Computer Systems Science and Engineering.
  5. Hafeezallah, A., Al-Dhamari, A.*, and Abu-Bakar, S. A. R. (2022). Multi-Scale Network with Integrated Attention Unit for Crowd Counting. Computers, Materials & Continua, 73, 3879–3903.
  6. Hafeezallah, A., Al-Dhamari, A.*, and Abu-Bakar, S. A. R. (2021). U-ASD Net: Supervised Crowd Counting Based on Semantic Segmentation and Adaptive Scenario Discovery. IEEE Access, 9, 127444-127459.
  7. Mohammed, M. S., Paraman, N., Ab Rahman, A. A. H., Ghaleb, F. A., Al-Dhamari, A., and Marsono, M. N. (2021). PEW: Prediction-Based Early Dark Cores Wake-up Using Online Ridge Regression for Many-Core Systems. IEEE Access, 9, 124087-124099.
  8. Al-Dhamari, A.*, Sudirman, R., and Mahmood, N. H. (2020). Transfer Deep Learning Along with Binary Support Vector Machine for Abnormal Behavior Detection. IEEE Access, 8, 61085-61095.
  9. Al-Dhamari, A.*, Sudirman, R., and Mahmood, N. H. (2021). Abnormal Behavior Detection Using Sparse Representations Through Sequential Generalization of K-means. Turkish Journal of Electrical Engineering & Computer Sciences, 29(1), 152-68.
  10. Al-Dhamari, A.*, Sudirman, R., Mahmood, N. H., Khamis, N. H., and Yahya, A. (2019). Online Video-Based Abnormal Detection Using Highly Motion Techniques and Statistical Measures. Telkomnika, 17(4), 2039-2047.
  11. Al-Dhamari, A.*, Sudirman, R., and Mahmood, N. H. (2017). Abnormal Behavior Detection in Automated Surveillance Videos: A Review. Journal of Theoretical & Applied Information Technology, 95(19).
  12. Al-Dhamari, A. K., and Darabkh, K. A. (2017). Block-Based Steganographic Algorithm Using Modulus Function and Pixel-Value Differencing. Journal of Software Engineering and Applications, 10(1), 56-77.
  13. Darabkh, K. A., Al-Dhamari, A., and Jafar, I. F. (2017). A New Steganographic Algorithm Based on Multi Directional PVD And Modified LSB. Information Technology and Control, 46(1), 16-36.
  14. Hiary, H., Sabri, K. E., Mohammed, M. S., and Al-Dhamari, A. (2016). A Hybrid Steganography System Based on LSB Matching and Replacement. International Journal of Advanced Computer Science and Applications (IJACSA), 7(9), 374-380.

B. Conference Papers

  1. Al-Dhamari, A.*, Hafeezallah, A. and Abu-Bakar, S. A. R. (2023). Motion Segmentation of Pedestrian Trajectories Using Angular Gaussian Mixture Mode. Proceedings of the 3rd International Conference on Big Data and Computational Intelligence (BDCI 2023), Tokyo, Japan. ACM
  2. Mohammed, M. S., Al-Dhamari, A., Ab Rahman, A. A. H., Paraman, N., Al-Kubati, A. A., and Marsono, M. N. (2019). Temperature-Aware Task Scheduling for Dark Silicon Many-Core System-on-Chip, in the 8th International Conference on Modeling Simulation and Applied Optimization (ICMSAO), Manama, Bahrain. IEEE.
  3. Al-Dhamari, A.*, Sudirman, R., Mahmood, N. H., Khamis, N. H., and Yahya, A. (2018). Online Video-Based Abnormal Detection Using Highly Motion Techniques and Statistical Measures. In the 3rd International Conference on Electrical, Electronic, Communication and Control Engineering (ICEECC), Johor Bahru, Malaysia.

Professional Activities

  • Publication committee: the 7th International Conference of Reliable Information and Communication Technology (IRICT 2023).
  • Presenting the research findings in the 3rd International Conference on Big Data and Computational Intelligence (BDCI 2023), Tokyo, Japan.
  • A judge for 2021 IEEE Signal Processing Society Summer-School (From Machine Learning to Deep Learning: A Computer Vision Perspective).
  • Hands-on facilitator for 2021 IEEE Signal Processing Society Summer-School on (From Machine Learning to Deep Learning: A Computer Vision Perspective).
  • Presenting the research findings in the 3rd International Conference on Electrical, Electronic, Communication and Control Engineering, Johor Bahru, Malaysia.
  • Extensive experience in reviewing submitted manuscripts for prestigious journals such as IEEE, Springer, Elsevier, and MDPI.

Professional Associations

  • Registered with Malaysia Board of Technologists, Malaysia (MBOT)
  • Member of Association for Computing Machinery (ACM)
  • Member of Institute of Electrical and Electronics Engineers (IEEE).