Dr. Metwally Rashad, Prince Prince Sattam Bin Abdulaziz University, Saudi Arabia
Dr. Metwally Rashad is an Assistant Professor of Computer Science at the Faculty of Computers & Artificial Intelligence, Benha University, Egypt. He earned his Ph.D. in Computer Science from the University of Pannonia, Hungary, specializing in image processing and computer vision. With over 18 years of academic experience, he has taught a wide range of courses, including artificial intelligence, medical image processing, and computer graphics. Dr. Rashad has published extensively in high-impact journals and conferences, with notable work in object recognition, video summarization, and medical image retrieval. He has supervised numerous M.Sc. and Ph.D. students and actively contributes to research in AI, deep learning, and data mining. He holds leadership roles within his faculty, including executive director of the IT unit and faculty board member. A recipient of international publishing awards, Dr. Rashad is a committed researcher with global exposure and a strong background in both teaching and applied research.
Publication Profile
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🎓 Academic Qualifications
Dr. Metwally Rashad has pursued a progressive academic path rooted in mathematics and computer science. He earned his B.Sc. in Mathematics in 2002 from the Faculty of Science at Benha University, Egypt. In 2006, he completed a two-year Diploma in Computer Science from the Institute of Statistical Studies and Research (ISSR) at Cairo University, reflecting his growing interest in computational systems. Building on this foundation, he completed a Pre-master program in Computer Science at Benha University in 2008. His M.Sc., awarded in 2013 from the same institution, focused on string representation for efficient mining and searching over string databases. Dr. Rashad advanced his academic career further by earning a Ph.D. in Computer Science from the University of Pannonia, Hungary, in 2018. His doctoral research centered on video-based object retrieval and recognition using lightweight devices, aligning with cutting-edge developments in image processing and computer vision. His qualifications demonstrate a consistent dedication to both theoretical and applied computing sciences.
👨🏫 Professional Positions
Dr. Metwally Rashad has built a robust academic career through progressive roles at Benha University, Egypt. He began as a Demonstrator in the Department of Mathematics (Computer Science), Faculty of Science, from 2004 to 2009. In 2010, he transitioned to the Faculty of Computers & Informatics, continuing as a Demonstrator in the Information System Department until 2011. His dedication and academic growth led to his promotion as an Assistant Lecturer in the same department, a position he held from 2012 to 2017. In 2018, Dr. Rashad was appointed Assistant Professor in the Information System Department, Faculty of Computers & Artificial Intelligence. Since April 2020, he has been serving as an Assistant Professor in the Computer Science Department of the same faculty. Throughout his tenure, Dr. Rashad has demonstrated strong commitment to research, education, and leadership, contributing significantly to the development of the academic and research landscape at Benha University.
🔬 Research Interests
Dr. Metwally Rashad’s research interests encompass a wide range of cutting-edge topics in computer science and artificial intelligence. He specializes in exact and approximate matching, with a strong focus on similarity search and similarity join techniques, which are vital for efficient data comparison and retrieval. His work also explores data cleaning and integration methods, enhancing the quality and usability of large datasets. Dr. Rashad is deeply engaged in database systems and data mining, aiming to extract meaningful patterns from complex data structures. His research extends into the fields of cryptography, image processing, and computer vision, where he applies innovative techniques for object recognition and image analysis. Additionally, he is active in machine learning and deep learning, leveraging these technologies to solve real-world problems. A significant portion of his work involves video processing and artificial intelligence applications, making his contributions highly relevant in today’s data-driven and multimedia-intensive landscape
📘 Teaching
Dr. Metwally Rashad has taught a wide array of undergraduate and postgraduate courses in computer science and artificial intelligence, reflecting his deep expertise and versatility as an academic. His teaching portfolio includes foundational programming languages such as C++, Java, and Matlab, as well as critical subjects like Data Structures, Algorithms, and File Structures. He has also delivered advanced courses in Artificial Intelligence, Machine Learning, and Expert Systems, along with specialized topics like Image Processing, Medical Image Processing, and Computer Vision. Dr. Rashad’s instruction covers essential theoretical areas, including Theory of Computation, Logic Design, Discrete Mathematics, and Structural Programming. He is also experienced in teaching Information Systems, Database Design, Compiler Construction, and Security. His course offerings further extend to emerging and interdisciplinary areas like Information Visualization, Multimedia, Computer Graphics, and Operations Research. This comprehensive teaching background underscores his commitment to fostering technical excellence and innovation among his students.
🏅 Grants and Awards
Dr. Metwally Rashad has been recognized for his impactful research through multiple prestigious awards and grants. He was honored with the International Publishing Prize and Citations from Benha University on two separate occasions—first in January 2018 and again in July 2020—in acknowledgment of his significant contributions to high-impact scientific publications. In addition to these accolades, Dr. Rashad secured a post-doctoral research grant from the Tempus Public Foundation (TPF), supporting his research stay at the Department of Electrical Engineering and Information Systems, Faculty of Information Technology, University of Pannonia, Hungary, from February to May 2020. These recognitions not only highlight his excellence in publishing and international collaboration but also reflect his sustained commitment to advancing knowledge in computer science and artificial intelligence. His achievements stand as a testament to his academic leadership and contribution to global research innovation.
🔍 Research Focus
Dr. Metwally Rashad’s research primarily centers around Artificial Intelligence (AI), Computer Vision, and Data-Driven Healthcare Systems, with a strong interdisciplinary approach linking image processing, machine learning, and information retrieval. His most cited works involve irony detection in Arabic tweets, medical image retrieval, video object recognition, and string similarity join algorithms—reflecting his deep engagement with natural language processing (NLP), deep learning, and visual data analytics. A recurring theme in his publications is the development of lightweight, efficient models for video summarization, emotion recognition, and 3D object retrieval, optimized for low-resource environments. Additionally, he contributes to healthcare technologies through AI-assisted diagnosis, content-based retrieval in medical imaging, and melanoma detection using deep neural networks. His research aligns with the growing global emphasis on AI for smart healthcare, secure cloud computing, and intelligent multimedia processing, making him highly suitable for recognition in advanced computational and AI-powered research categories
Publication Top Notes
📘 BENHA@ IDAT: Improving Irony Detection in Arabic Tweets using Ensemble Approach – Cited by 31 (2019) 🧠🗣️📊
📘 RbQE: An Efficient Method for Content-Based Medical Image Retrieval Based on Query Expansion – Cited by 17 (2023) 🖼️🧬📥
📘 PreJoin: An Efficient Trie-Based String Similarity Join Algorithm – Cited by 9 (2012) 🧵📚🔍
📘 View Centered Video-Based Object Recognition for Lightweight Devices – Cited by 8 (2016) 🎥🔎📱
📘 CCNN-SVM: Emotion Recognition with Custom CNNs and SVM – Cited by 7 (2024) 😊📈🧠
📘 Content-Based Medical Image Retrieval Based on Deep Features Expansion – Cited by 7 (2022) 🏥🧠🔎
📘 Use of IMUs for Video Object Retrieval in Lightweight Devices – Cited by 7 (2017) 🎥📡🤖
📘 Lightweight Active Object Retrieval with Weak Classifiers – Cited by 6 (2018) 📽️📊🧠
📘 Lightweight Video Object Recognition Based on Sensor Fusion – Cited by 5 (2015) 📹📡🔀
📘 Modern Techniques in Content-Based Medical Image Retrieval: A Survey – Cited by 4 (2022) 🏥📚📈
📘 Active Multiview Recognition with Hidden Markov Temporal Support – Cited by 4 (2021) 🧠📽️🔁
📘 Efficient String Edit Similarity Join Algorithm – Cited by 4 (2017) 🧵📝⚙️
📘 Fusion of Optical and Orientation Info in Markovian Framework for 3D Object Retrieval – Cited by 4 (2017) 🎥📐📊
📘 Automatic Melanoma Detection Using Deep Neural Networks – Cited by 2 (2024) 🧬🧠⚕️