rasha shoitan
About me
Dr. Rasha Shoitan is an Associate Professor of Electronics Engineering with a deep passion for artificial intelligence and its applications in real-world challenges. She earned her Ph.D. in Electronics Engineering from Helwan University, focusing on improved image compression using compressive sensing. Her academic journey spans over 15 years, combining research, teaching, and active participation in national innovation projects.
Dr. Shoitan is currently affiliated with the Electronic Research Institute (ERI) and the University of Hertfordshire (hosted by the Global Academy Foundation), where she teaches advanced AI subjects such as Social and Collective AI and Intelligent Adaptive Systems. Before this, she held teaching roles at several institutions including the Modern University for Technology and Information (MTI), where she taught foundational courses such as digital signal processing, electronic circuits, and digital image processing, helping students build a strong technical base.
Her research focuses on AI-driven systems for computer vision, image manipulation detection, video analysis, and signal processing. She has contributed significantly to various research projects, such as intelligent water management using IoT, AI-enhanced video libraries, and bioinformatics modeling using neural networks and genetic algorithms. These efforts have resulted in numerous publications in top-tier journals and conferences. Dr. Shoitan combines technical depth with an ongoing commitment to innovation, earning her the Scientific Excellence Award at ERI in 2024. She is also a member of the AI Management System (AIMS) Committee at ERI, contributing to initiatives that promote responsible and ethical AI governance within the institute. Her work continues to explore the intersection of AI, sustainability, and digital transformation, aiming to create intelligent systems that solve pressing societal problems.
Dr. Rasha Shoitan is an Associate Professor of Electronics Engineering with a deep passion for artificial intelligence and its applications in real-world challenges. She earned her Ph.D. in Electronics Engineering from Helwan University, focusing on improved image compression using compressive sensing. Her academic journey spans over 15 years, combining research, teaching, and active participation in national innovation projects.
Dr. Shoitan is currently affiliated with the Electronic Research Institute (ERI) and the University of Hertfordshire (hosted by the Global Academy Foundation), where she teaches advanced AI subjects such as Social and Collective AI and Intelligent Adaptive Systems. Before this, she held teaching roles at several institutions including the Modern University for Technology and Information (MTI), where she taught foundational courses such as digital signal processing, electronic circuits, and digital image processing, helping students build a strong technical base.
Her research focuses on AI-driven systems for computer vision, image manipulation detection, video analysis, and signal processing. She has contributed significantly to various research projects, such as intelligent water management using IoT, AI-enhanced video libraries, and bioinformatics modeling using neural networks and genetic algorithms. These efforts have resulted in numerous publications in top-tier journals and conferences. Dr. Shoitan combines technical depth with an ongoing commitment to innovation, earning her the Scientific Excellence Award at ERI in 2024. She is also a member of the AI Management System (AIMS) Committee at ERI, contributing to initiatives that promote responsible and ethical AI governance within the institute. Her work continues to explore the intersection of AI, sustainability, and digital transformation, aiming to create intelligent systems that solve pressing societal problems.
Degrees:
Rasha Shoitan, Zaki Nossair, Ibrahim Isamil, and Ahmed Tobal, “Hybrid wavelet measurement matrices for improving compressive imaging,” Signal Image Video Process., pp. 1–8, Apr. 2016.
Rasha Shoitan, Zaki Nossair, Ibrahim Isamil, and Ahmed Tobal, “Performance improvement of the decoding side of the BCS-SPL technique ,” Proceedings of the International Conference on New Paradigms in Electronics & Information Technology (PEIT), Alexandria, Egypt, 2017
Rasha Shoitan, Zaki Nossair, Ibrahim Isamil, and Ahmed Tobal, “Performance Improvement of Orthogonal Matching Pursuit Based on Wilkinson Matrix for Block Compressive Sensing,” Proceedings of the 1st International Conference on Computer Applications & Information Security (ICCAIS) , Riyadh, Saudi Arabia , 2018.
Rasha Shoitan, Zaki Nossair, Ibrahim Isamil, and Ahmed Tobal, “Improving the reconstruction efficiency of the sparsity adaptive matching pursuit based on Wilkinson matrix,” Front. Inf. Technol. Electron. Eng., pp 503-512, Apr.2018.
Rasha Shoitan, Zaki Nossair, Ibrahim Isamil, and Suzan M. Elshoura, "Image Recovery from Incomplete Walsh Measurements Based on Orthogonal Matching Pursuit," 2019 14th International Conference on Computer Engineering and Systems (ICCES), Cairo, Egypt, 2019, pp. 3-10.
Rasha Shoitan, Mona M.Moussa , Suzan M. Elshoura,” A robust video watermarking scheme based on Laplacian pyramid, SVD, and DWT with improved robustness towards geometric attacks via SURF”. Multimed Tools Appl (2020). https://doi.org/10.1007/s11042-020-09258-x
Mona M.Moussa , Rasha Shoitan, “Object-based Video Synopsis Approach using Particle Swarm Optimization”, Signal Image Video Process, 15, pp. 761–768 2021
Rasha Shoitan, Sawsan Morkos Gharghory “Compressive Sensing Theory for Improving the Robustness and the Security of the Discrete Wavelet Transform-Singular Value Decomposition Watermarking Scheme “ journal of computer science, 17(4), pp. 414-426, 2021
Rasha Shoitan, Mona M.Moussa “Unsupervised cosegmentation model based on saliency detection and optimized HSV features of superpixels” journal of computer science,17(7), pp.670-682,2021
Mona M. Moussa, Rasha Shoitan, Mohamed.S.Abdallah “ Efficient Common objects Localization based on Deep Hybrid Siamese Network”, Journal of Intelligent and Fuzzy Systems 41(2):3499-3508, 2021
Rasha Shoitan, Mona M. Moussa, and Heba A. E. Nemr. "Attribute Based Spatio-temporal Person Retrieval in Video Surveillance." Alexandria Engineering Journal 63, (2023): 441-454.
Rasha Shoitan, Mona M. Moussa, Sawsan M. Gharghory, Heba A. Elnemr, Young Cho, and Mohamed S. Abdallah. "User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions." Sensors 23, no. 3 (2023): 1521.
Abd-elmegeid Amin Ali, Mohamed Mashhour, Ahmed S. Salama, Rasha Shoitan, and Hassan Shaban. "Development of an Intelligent Personal Assistant System Based on IoT for People with Disabilities." Sustainability 15, no. 6 (2023): 5166.
Azza Elsayed Ibrahim, Rasha Shoitan, Mona M. Moussa, Heba A. Elnemr, Young Im Cho and Mohamed S. Abdallah, “Object Detection-based Automatic Waste Segregation using Robotic Arm” International Journal of Advanced Computer Science and Applications (IJACSA), 14(6), 2023.
Ahmed S. Salama, Rasha Shoitan, Mohamed S. Abdallah, Young Im Cho, Ahmad M. Nagm. A robust algorithm for digital image copyright protection and tampering detection: Employing DWT, DCT, and blowfish techniques. Traitement du Signal, Vol. 40, No. 5 (2023), pp. 2019-2027.
Ahmad M. Nagm, Mona M. Moussa, Rasha Shoitan, Ahmed Ali,
Mohamed Mashhour, Ahmed S. Salama, and Hamada I. AbdulWakel “Detecting Image Manipulation with ELA-CNN Integration: A Powerful Framework for Authenticity Verification”, PeerJ Computer Science.
Rasha Shoitan, Mona M. Moussa, Nahed Tawfik, “Exploring generative artificial intelligence: A comprehensive guide”, Accepted, Peerj computer science.
Moussa, Mona, and Rasha Shoitan. "Advancements in Image Integrity Verification Techniques and Challenges in AI-Driven Forensics." Digital Forensics in the Age of AI, edited by Marwan Omar and Hewa Majeed Zangana, IGI Global, 2025, pp. 281-320.
Hassan I. Sayed Ahmed, Rasha Shoitan, Ghada F. Elkabbany, Mona M. Moussa, Young-Im Cho, Mohamed Sameer, “Reinforcing Query-based Surveillance Synopsis Security through Distributed Computing," JOURNAL OF THEORETICAL AND APPLIED INFORMATION TECHNOLOGY, 2(24), 2024.
A. El-Fiky, N. El-Fishawy, A. A. Ein-Shoka, R. M. Bayoumi, and R. Shoitan, “Spatiotemporal violence detection in surveillance video via CNN–ConvLSTM with temporal attention fusion,” Results in Engineering, manuscript under review.
A. S. Salama, H. I. AbdulWakel, E. A. Aldakheel, M. M. Moussa, R. Shoitan, and A. M. Nagm, “Deep spatiotemporal human activity recognition using an optimized 3D CNN model,” manuscript under review.