Zinah Saeed | Deep Learning | Best Researcher Award

Ms. Zinah Saeed | Deep Learning | Best Researcher Award

Universiti Sains Malaysia | Iraq

Saeed ZR is a dedicated researcher and academic with a strong background in computer science, networking technology, and innovative applications of artificial intelligence, currently pursuing his doctoral studies in computer science at the School of Computer Sciences, Universiti Sains Malaysia, after completing a master’s degree in networking technology at Universiti Teknikal Malaysia Melaka and a bachelor’s degree in computer science at Mustansiriyah University in Baghdad, building his academic journey on a foundation of technical expertise and analytical thinking, his research interests cover metaheuristic algorithms, artificial intelligence, deep learning, gesture recognition, assistive technologies, human–computer interaction, and networking security, he has contributed to the academic community with impactful publications including a hybrid improved IRSO–CNN algorithm for accurate recognition of dynamic gestures in Malaysian sign language, a systematic review on systems-based sensory gloves for sign language pattern recognition, and research on improving cloud storage security using three layers of cryptography algorithms, his professional journey includes significant teaching experience as a lecturer at the Iraqi Police Academy where he worked to advance education and training, and his ongoing research and doctoral studies have strengthened his ability to design, implement, and test intelligent systems addressing real-world challenges, his technical skills encompass proficiency in computer software, Microsoft Office applications, and operating systems across Windows and Mac environments, alongside practical programming expertise in Python for scripting and data processing, he is also experienced with widely used research and software tools such as Jupyter, Colab, Git, SPSS, and basic MATLAB, beyond his professional life he nurtures a passion for reading, research, and continuous learning, qualities that support his growth as a thoughtful academic and innovative researcher, his multidisciplinary focus, combined with a strong commitment to impactful scientific contributions, reflects a future-oriented career in advancing artificial intelligence and human-centered technologies.

Profile: Google Scholar

Featured Publications:

Saeed, Z. R., Ibrahim, N. F., Zainol, Z. B., & Mohammed, K. K. (2025). A hybrid improved IRSO–CNN algorithm for accurate recognition of dynamic gestures in Malaysian sign language. Journal of Electrical and Computer Engineering, 2025(1), 6430675.

Saeed, Z. R., Zainol, Z. B., Zaidan, B. B., & Alamoodi, A. H. (2022). A systematic review on systems-based sensory gloves for sign language pattern recognition: An update from 2017 to 2022. IEEE Access, 10, 123358–123377.

Saeed, Z. R., Zakiah Ayop, N. A., & Baharon, M. R. (2018). Improved cloud storage security using three layers cryptography algorithms. International Journal of Computer Science and Information Security, 16(10), 11–18.

 

Abebaw Agegne | Deep Learning | Best Researcher Award

Mr. Abebaw Agegne | Deep Learning | Best Researcher Award

Debark University | Ethiopia

Abebaw Agegne Engda is an Ethiopian scholar and academic who has devoted his professional career to the advancement of computer science education and research while fostering strong community engagement and service. He earned his Bachelor of Science degree in Computer Science from Debre Tabor University with high academic distinction, completing his studies with a focus on programming, systems, and applied computing. He later pursued a Master of Science degree in Computer Science at the University of Gondar, where he further deepened his knowledge of computational theory, advanced software systems, and the practical applications of computer science in solving real-world challenges. His academic excellence is demonstrated by his strong cumulative performance in both degrees, which reflect a commitment to rigor and perseverance. Professionally, he began his teaching journey as an Assistant Lecturer at Debark University, where he taught undergraduate computer science courses and contributed to shaping the foundational knowledge of young scholars. Later, he advanced to the position of Lecturer at Debark University, where he continues to teach computer science students across a variety of specializations, delivering core programming, system analysis, and applied computing courses while contributing to other departments with harmonized curriculum approaches. His students have consistently benefited from his structured teaching style, with many advancing to careers in high-level companies and industries, demonstrating the practical effectiveness of his teaching methodologies. He is capable of teaching a wide range of programming languages and has also been recognized for his leadership within his department, guiding academic processes, curriculum harmonization, and student development initiatives. His research works and community service contributions are documented and accessible through his ORCID profile, reflecting his engagement with both scholarly and societal responsibilities. Beyond academics, he is a person of discipline, patience, and strong work habits, qualities that enhance his ability to serve effectively in challenging environments and to maintain positive relationships with colleagues and students. He is fluent in Amharic and English, which allows him to engage in both local and international academic contexts, and his hobbies such as reading, traveling, counseling, and cultural exploration reflect a personality committed to lifelong learning, empathy, and service to others. Overall, his biography presents the portrait of a self-respecting, fair, and hardworking educator who combines academic achievement, teaching excellence, research contributions, and community service, making him a valuable asset in the advancement of computer science education in Ethiopia and beyond.

Profile: Orcid

Featured Publications:

Asnake, N. W., Ayalew, A. M., & Engda, A. A. (2025). Detection of oral squamous cell carcinoma cancer using AlexNet on histopathological images. Discover Applied Sciences.

Ayele, M. K., Baye, G. A., Yesuf, S. H., Engda, A. A., & Mitiku, E. T. (2025). Predicting stunting status among under five children in Ethiopia using ensemble machine learning algorithms. Scientific Reports.

Engda, A. A., Salau, A. O., & Ajala, O. (2025). Classical machine learning approaches for early hypertension risk prediction: A systematic review. Applied AI Letters.

Engda, A. A., Zewale, G. E., Mihret, B. G., & Adane, A. T. (2025). Developing pneumonia detection model using chest X-ray images: Deep learning approach. Preprint.

Engda, A. A. (2025). Detection of oral squamous cell carcinoma cancer using AlexNet on histopathological images. Conference paper.

Engda, A. A. (2025). Development of a case-based reasoning system for onion disease diagnosis and treatment. Proceedings of the IEEE International Conference on Emerging and Sustainable Technologies for Power and ICT in a Developing Society.