Dr. Sakher Ghanem

Research Interest:

• Sign Language Recognition.

• Computer Vision.

• Machine Learning.

Educational Background:

• Doctor of Philosophy in Computer Science (August 2020). 

  • The University of Texas at Arlington, Arlington, Texas, USA.

  • Dissertation Title: “Hand-Over-Face Segmentation”.

• Master of Science in Computer Science (November 2008). 

  • King Abdulaziz University, Jeddah, Saudi Arabia.

  • Thesis Title: “An Avatar Based Natural Arabic Sign Language Generation System for Deaf People”.

• Bachelor of Science in Computer Science (May 2002). 

  • King Abdulaziz University, Jeddah, Saudi Arabia.

Publications:

• Alzubaidi, A., & Ghanem, S. (2025, May). Arabic SMS Spam Detection. In 2025 International Conference on Innovation in Artificial Intelligence and Internet of Things (AIIT) (pp. 1-6). IEEE.

• Alayaid, N. H., Albaidhani, M. O., Alghamdi, A. M., Sindi, R. A., Alharbi, A. S., & Ghanem, S. (2025, May). Deep learning-based vegetation monitoring using the NDVI index. In 2025 International Conference on Innovation in Artificial Intelligence and Internet of Things (AIIT) (pp. 1-8). IEEE.

• Baalawi, A. H., Ghanem, S., & Alqahtani, M. M. (2025, April). Detecting Depression in Arabic Texts Using AI Techniques. In 2025 4th International Conference on Computing and Information Technology (ICCIT) (pp. 584-591). IEEE.

• Tian, J., Alanazy, S., Bokhary, A., Alharthi, S., & Ghanem, S. (2022, December). Measuring Influencing Factors of API Usability. In 2022 International Conference on Computational Science and Computational Intelligence (CSCI) (pp. 1889-1894). IEEE.

• Ghanem, S., Dillhoff, A., Imran, A., & Athitsos, V. (2020, June). Hand over face segmentation using MPSPNet. In Proceedings of the 13th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 257-264). ACM.

• Ghanem, S., Imran, A., & Athitsos, V. (2019, June). Analysis of hand segmentation on challenging hand over face scenario. In Proceedings of the 12th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 236-242). ACM. (Dataset link)

• Alesawi, S., & Ghanem, S. (2019, February). Overcome Heterogeneity Impact in Modeled Fork-Join Queuing Networks for Tail Prediction. In 2019 International Conference on Computing, Networking and Communications (ICNC) (pp. 270-275). IEEE.

• Ghanem, S., Conly, C., & Athitsos, V. (2017, June). A survey on sign language recognition using smartphones. In Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 171-176). ACM.