Mohammed M Alenazi | Computer Science and Artificial Intelligence | Best Researcher Award

Dr. Mohammed M Alenazi | Computer Science and Artificial Intelligence | Best Researcher Award

Assistance Professor | University of Tabuk | Saudi Arabia

Dr. Mohammed M. Alenazi is an Assistant Professor of Computer Engineering at the University of Tabuk, Saudi Arabia, whose research focuses on the intersection of energy-efficient communication networks, machine learning, and distributed systems. His work advances intelligent computing architectures that optimize performance, reduce energy consumption, and enable sustainability in next-generation networks. Dr. Alenazi has contributed to several impactful studies, including energy-efficient neural network embedding in IoT over passive optical networks, distributed machine learning in cloud–fog environments, and AI-driven frameworks for 6G-IoT-based remote cardiac monitoring. His research extends to federated learning for low-latency IoT communications, hybrid cloud edge architectures for real-time cryptocurrency forecasting with blockchain integration, and machine learning-optimized energy management for resilient residential microgrids with electric vehicle integration. His scholarly output, cited over 50 times with an h-index of 4 and i10-index of 3, reflects growing recognition in the domains of sustainable networking and intelligent systems. Dr. Alenazi’s work combines AI, IoT, and cloud–fog computing to create adaptive, energy-aware solutions for smart environments, healthcare, and industrial systems. Through his innovative contributions, he continues to enhance the efficiency, reliability, and intelligence of modern communication infrastructures, positioning his research at the forefront of AI-powered green networking and distributed intelligence for the evolving digital ecosystem.

Profiles : ORCID | Scopus | Google Scholar | ResearchGate

Featured Publications

1. Alenazi, M. M., Yosuf, B. A., El-Gorashi, T., & Elmirghani, J. M. H. (2020). Energy efficient neural network embedding in IoT over passive optical networks. Cited By : 13

2.Yosuf, B. A., Mohamed, S. H., Alenazi, M. M., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2021). Energy-efficient AI over a virtualized cloud fog network. Cited By : 12

3.Alenazi, M. M., Yosuf, B. A., Mohamed, S. H., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2021). Energy-efficient distributed machine learning in cloud fog networks. Cited By : 10

4.Banga, A. S., Alenazi, M. M., Innab, N., Alohali, M., Alhomayani, F. M., Algarni, M. H., et al. (2024). Remote cardiac system monitoring using 6G-IoT communication and deep learning. Cited By : 6

5.Alenazi, M. M., Yosuf, B. A., Mohamed, S. H., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2022). Energy efficient placement of ML-based services in IoT networks. Cited By : 4

Ruzayn Quaddoura | Computer Science | Best Researcher Award

Assoc. Prof.Dr.Ruzayn Quaddoura | Computer Science | Best Researcher Award

Zarqa University, Jordanian

Dr. Ruzayn Quaddoura 🇯🇴 is a renowned academic and researcher in the field of computer science, specializing in combinatorial optimization and algorithmic graph theory. he has over two decades of teaching and research experience . Currently serving as Assistant Professor at Zarqa University in Jordan , he has also held teaching positions in Saudi Arabia 🇸🇦, France 🇫🇷, and Syria 🇸🇾. Dr. Quaddoura has made significant contributions to the study of NP-hard problems, scheduling algorithms, and digraph structures . He has authored numerous peer-reviewed publications in prestigious journals and conferences worldwide . Multilingual in Arabic, English, and French , he actively engages in academic committees, technical boards, and student mentorship. His dedication to quality education and advanced algorithm research positions him as a leading voice in theoretical computer science .

🔹Professional Profile

ORCID

🔹 Education & Experience

Dr. Quaddoura’s academic foundation was laid at Damascus University 🇸🇾, where he earned his Bachelor’s and Postgraduate Diploma in Mathematics . He then pursued a Diploma in French Language 🇫🇷 and later completed an MSc (DEA) in Operations Research – Combinatorial Optimization at INPG, Grenoble . He culminated his academic training with a PhD in Algorithmic Graph Theory from the University of Picardie Jules Verne, France .His professional journey began as a lecturer in Syria and France, before moving into Assistant Professor roles at Princess Sumaya University, Zarqa University, and King Abdulaziz University . Since 2011, he has been a key faculty member at Zarqa University’s Faculty of Information Technology. His teaching areas include algorithms, data structures, discrete mathematics, and compilers . His global academic experience and strong theoretical background reflect a career devoted to advancing computer science education and research .

🔹 Professional Development 

Throughout his career, Dr. Quaddoura has actively contributed to academic growth, institutional leadership, and scholarly collaboration . He has served on various academic committees at Zarqa University, including the Scientific Committee, Study Plan Committee, and Course Equivalence Committee. As Chairman of Exams and Committee Leader, he has shaped curriculum and assessment strategies with excellence.He played similar roles at King Abdulaziz University, contributing to master’s program oversight and curriculum development in computing and information technology . His refereeing activities include serving on the technical committees of prominent journals and conferences like IAJIT and ACIT . Additionally, he managed the Colleges of Computing and Information Society office in 2015, demonstrating organizational and strategic leadership.His professional footprint showcases not only academic rigor but also collaborative leadership, quality assurance, and international engagement in the computing education community .

🔹 Research Focus Category 

Dr. Ruzayn Quaddoura’s primary research lies in Theoretical Computer Science, focusing on Combinatorial Optimization, Algorithmic Graph Theory, and Complexity Theory . His work explores the deep structure of graphs, creating efficient solutions to NP-hard problems using novel algorithmic techniques . From linear-time scheduling algorithms for specific graph families to optimization in series-parallel digraphs and bipartite graphs, his research bridges abstract theory and real-world computational problems .He has also extended his expertise to applied fields such as the Internet of Things (IoT), encryption, and machine learning in wildfire detection . His publications in top-tier journals like IAJIT, Algorithms, and Symmetry highlight his contributions to both pure and applied research .Dr. Quaddoura’s innovative approaches to graph decomposition, structural analysis, and algorithmic efficiency contribute significantly to solving modern computing challenges through mathematical elegance and logical precision .

🔹 Awards and Honors 

 Dr. Quaddoura’s academic excellence has been recognized through several prestigious awards and honors. He earned a First Rank Honor Certificate from Damascus University in 1992 for academic distinction in Mathematics . He received a scholarship from INPG (France) for his MSc in Combinatorial Optimization and another scholarship from Picardie Jules Verne University to pursue his PhD in Theoretical Computer Science , In 2014, he was honored with a Recognition Paper Award from the World of Computer Science and Information Technology Journal for his innovative algorithm on induced matchings in bipartite graphs .These accolades reflect his commitment to research excellence, international academic collaboration, and impactful contributions to the field of computer science 🌍🔬.His scholarly achievements not only affirm his status as a leading researcher but also inspire a generation of students and scientists dedicated to algorithmic innovation and problem-solving .

🔹Publication of Top Notes

1. The Clique-Width of Minimal Series-Parallel Digraphs

Authors: Frank Gurski, Ruzayn Quaddoura
Year: 2025
Citation: Algorithms, 2025-05-28. DOI: 10.3390/a18060323

2.Early Wildfire Smoke Detection Using Different YOLO Models

Authors: Yazan Al-Smadi, Mohammad Alauthman, Ahmad Al-Qerem, Amjad Aldweesh, Ruzayn Quaddoura, Faisal Aburub, Khalid Mansour, Tareq Alhmiedat
Year: 2023
Citation: Machines, 2023. DOI: 10.3390/machines11020246

3. Internet of Things Protection and Encryption: A Survey

Authors: Ghassan Samara, Ruzayn Quaddoura, M. I. Al-Shalout, K. AL-Qawasmi, G. A. Besani
Year: 2022
Citation: arXiv, 2022. DOI: 10.48550/arxiv.2204.04189

4.Scheduling UET-UCT DAGs of Depth Two on Two Processors

Authors: Ruzayn Quaddoura, Ghassan Samara
Year: 2022
Citation: arXiv, 2022. DOI: 10.48550/arxiv.2203.15726

5. Scheduling UET-UCT DAGs of Depth Two on Two Processors

Authors: Ruzayn Quaddoura, Ghassan Samara
Year: 2021
Citation: 22nd International Arab Conference on Information Technology (ACIT), 2021. DOI: 10.1109/ACIT53391.2021.9677100

6.On 2-Colorability Problem for Hypergraphs with P₈-Free Incidence Graphs

Authors: Ruzayn Quaddoura
Year: 2020
Citation: International Arab Journal of Information Technology, 2020. DOI: 10.34028/iajit/17/2/14

🧾 Conclusion

Dr. Ruzayn Quaddoura is highly suitable for the Best Researcher Award. His research exhibits a rare balance of theoretical depth and practical relevance, particularly in the areas of graph theory, AI for environmental monitoring, and cybersecurity. His ongoing contributions to both academia and applied science solidify his standing as a leading and impactful researcher deserving of recognition.