Mohamed El-Eiemy is a Professor with more than 20 years of experience in Research and Teaching Information Management and Analysis. He has been employed in leading universities in MENA and Europe during his career with a highly cited publication profile and numerous research and education projects.
Mohamed El-Eliemy is an expert who has acquired outstanding experience working at the top IT strategic management in very large enterprises where he has participated in the IT strategic vision of digital transformation. Mohamed El-Eliemy has also participated in and led teams in several IT projects in Health, Banking, and Education sectors.
EDUCATION
PhD in Computer Science, FSU University of Jena Germany 2010
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Information Systems, Computer Networks and Communications, Artificial Intelligence
43
Scopus Publications
Scopus Publications
Weakly Supervised Deep Learning for Arabic Tweet Sentiment Analysis on Education Reforms: Leveraging Pre-Trained Models and LLMs with Snorkel Alanoud Alotaibi, Farrukh Nadeem, Mohamed Hamdy IEEE Access, 2025 This study introduces a novel approach to sentiment classification of Arabic tweets regarding educational reforms in Saudi Arabia. The complexity of the Arabic language, with its numerous dialects, poses challenges for natural language processing tasks, particularly when large volumes of data require manual annotation. To overcome the limitations of traditional labeling methods, we developed a weakly supervised learning framework that combines LLMs (GPT-3.5) and pre-trained language models (MarBERT and XLM-RoBERTa) to generate high-quality weakly labeled training data using the Snorkel framework. We fine-tuned the AraBERT model with this weakly labeled data for sentiment classification. Our experimental results demonstrated the effectiveness of the proposed approach, achieving 83% precision, 76% recall, and an 85% F1 score in classifying tweets as positive, negative, or neutral. Comparative analysis showed that GPT-3.5 outperformed Llama 2 in prompting tasks, and our weakly supervised model surpassed baseline machine learning methods. These findings highlight the potential of weakly supervised learning in analyzing public opinion on Arabic social media platforms without relying on large, labeled datasets.
Enabling Moving Services in Enterprise Computing Mohamed Hamdy, Ahmed Samy, Mohamed Dahab, Khaled ElBahnasy 2025 2nd International Conference on Advanced Innovations in Smart Cities Icaisc 2025, 2025 Recently., ICT enables new models for enterprise applications and resources such as Cloud computing. The common business applications and resources management within an enterprise compose the enterprise computing environment. The wireless and mobile infrastructure support in an enterprise computing environment for mobile applications represents the common feature of the modern enterprise computing. This work proposes a model for utilizing the role of service mobility or what is called (in this work) the “moving services”” in an intermediary layer between cloud data service providers and their clients inside an enterprise computing environment. The model enables a better service mobility coverage for an enterprise. This intermediary layer introduces a required Edge/Fog computing layer that uses the wireless infrastructure to support a better data service allocation for the mobile clients and applications. This work considers the integration between Cloud Data services and their replicas inside enterprise environment. Moreover., the infrastructure of wireless enterprise networks and the challenges of deploying this model are introduced and discussed.
Selfish-Free Influential Nodes Detection in Mobile Social Networks Doaa AbdelMohsen, Tamer Abdelkader, Mohamed Hamdy, Khaled ElBahnasy 2025 2nd International Conference on Advanced Innovations in Smart Cities Icaisc 2025, 2025 Mobile networks where users group in communities based on their interests, and disseminate data mainly to their community using their mobile devices, are called Mobile Social Networks (MSN). However, the efficiency of data dissemination becomes a challenging problem in these networks. Using influential users can improve the efficiency of data dissemination. An influential user should have an effective activity on the network and influence other users. The participation behavior of nodes in the network dramatically affects the detection process of influential nodes. Self-sufficient nodes who selectively participate in the dissemination of data in the network may reduce the influence of the other nodes. This paper proposes detecting influential nodes that consider the negative effects of selfish behavior. The performance analysis of the proposed selfish-free influential node detection protocol is presented by comparing it to another one that does not consider the selfishness problem. This comparison shows that the proposed protocol achieves efficiency up to 30% in a environment of selfish behavior.
Arabic Stock-News Sentiments and Economic Aspects using BERT Model Eman Alasmari, Mohamed Hamdy, Khaled H. Alyoubi, Fahd Saleh Alotaibi International Journal of Advanced Computer Science and Applications, 2023 — Stock-market news sentiment analysis (SA) aims to identify the attitudes of the news of the stock on the official platforms toward companies’ stocks. It supports making the right decision in investing or analysts’ evaluation. However, the research on Arabic SA is limited compared to that on English SA due to the complexity and limited corpora of the Arabic language. This paper develops a model of sentiments to predict the polarity of Arabic stock news in microblogs based on Machine Learning and Deep Learning approaches. Also, it aims to extract the reasons which lead to polarity categorization as the main economic causes or aspects based on semantic unity. Therefore, this paper presents an Arabic SA approach based on the logistic regression model and the Bidirectional Encoder Representations from Transformers (BERT) model. The proposed model is used to classify articles as positive, negative, or neutral. It was trained based on data collected from an official Saudi stock-market article platform that was later preprocessed and labeled. Moreover, the economic reasons for the articles based on semantic unit, divided into seven economic aspects to highlight the polarity, were investigated. The supervised BERT model obtained 88% article classification accuracy based on SA, and the unsupervised mean Word2Vec encoder obtained 80% economic-aspect clustering accuracy.
Influence propagation in social networks: Interest-based community ranking model Nouran Ayman R. Abd Al-Azim, Tarek F. Gharib, Mohamed Hamdy, Yasmine Afify Journal of King Saud University Computer and Information Sciences, 2022 The driving force behind content dissemination in Social network (SN) is the users’ interest in the content, which is strongly reflected in their interactions. Obviously, user interest varies with the disseminated content. Consequently, the dynamic interest results in decomposing SN into dynamic user clusters “interest groups”. The objective of this work is to rank interest-based communities using influence propagation. The contribution of this work is threefold: First, to highlight the significance of the indirect influence among interest-based user groups. Second, to study its impact on content dissemination capability. Third, to propose an ultimate ranking model (UltRank) that uniquely considers direct and indirect influences which are reflected in a new reachability metric that considers: 1. Distance among interest groups. 2. Percentage of reachable interest groups. 3. Percentage of reachable nodes. UltRank model has been evaluated in comprehensive experiments. First, clustering quality perspective, the Silhouette coefficient for the identified interest groups is on average 0.996 and the Jaccard coefficient of 97% of different interest groups members equals 0. Second, ranking capability perspective, UltRank model can rank up to 91% of interest groups in SN. Finally, ranking effectiveness perspective, UltRank ranking list has a competing network coverage results against the other benchmark approaches.
Enabling Fog Complex Security Services in Mobile Cloud Environments Mohamed Hamdy, Safia Abbas, Doaa Hegazy Alexandria Engineering Journal, 2021 The security infrastructure in modern mobile cloud relays on a set of atomic security services like key distribution, and authentication services which are mostly deployed at the fog. A mobile node may provide a simple or an atomic security service. Complex security services are obtained by coordinating several atomic services at different nodes. In mobile fog environments, the availability of such services for the mobile nodes at the edge straggles challenging nature of the environment and then service availability is deeply affected. Complex security requirements require available several atomic services at the edge and fog levels. So, increasing atomic service availability is vital and enhances security features between the fog and the edge. In this work a proactive complex security service replication protocol for increasing availability of fog security services is proposed. The protocol is able to manage proactively replicas whenever they are requested. It is aware of the distributed resources at the edge nodes. Using an extensive simulation analysis, the protocol performance shows a better achieved availability and reasonable response time for complex security services in different configurations.
Cyber space security assessment case study Hanaa. M. Said, Rania El Gohary, Mohamed Hamdy, Abdelbadeeh M. Salem Cyber Security and Threats Concepts Methodologies Tools and Applications, 2018
On biclustering of gene expression data Mahmoud Mounir, Mohamed Hamdy 2015 IEEE 7th International Conference on Intelligent Computing and Information Systems Icicis 2015, 2016
A proposed security service set for VANET SOA Safi Ibrahim, Mohamed Hamdy, Eman Shaaban 2015 IEEE 7th International Conference on Intelligent Computing and Information Systems Icicis 2015, 2016
Text document annotation methods: Stat of art Iman Ismail, Walaa Gad, Mohamed Hamdy, Khaled Bahnsy 2015 IEEE 7th International Conference on Intelligent Computing and Information Systems Icicis 2015, 2016
Cyber space security assessment case study Hanaa. M. Said, Rania El Gohary, Mohamed Hamdy, Abdelbadeeh M. Salem Handbook of Research on Threat Detection and Countermeasures in Network Security, 2014
New service selection strategies for the Service Distribution Protocol for manets Proc of the Iadis Int Confs Informatics 2010 Wireless Applications and Computing 2010 Telecommunications Networks and Systems 2010 Part of the Mccsis 2010, 2010
Impact of heterogeneous mobility models on the service distribution protocol for manets Proc of the Iadis Int Confs Informatics 2010 Wireless Applications and Computing 2010 Telecommunications Networks and Systems 2010 Part of the Mccsis 2010, 2010
Leader election modes of the service distribution protocol for ad hoc networks Lecture Notes in Informatics Lni Proceedings Series of the Gesellschaft Fur Informatik Gi, 2009
An extended analysis of an interest-based service distribution protocol for mobile ad hoc networks Winsys 2008 International Conference on Wireless Information Networks and Systems Proceedings, 2008
A quality-of-service-aware genetic algorithm for the source routing in ad-hoc mobile networks Iceis 2003 Proceedings of the 5th International Conference on Enterprise Information Systems, 2003
Modified distributed quality-of-service routing in wireless mobile ad-hoc networks Proceedings of the Mediterranean Electrotechnical Conference MELECON, 2002