Zhaozhen Jiang | Computer Science | Best Research Article Award

Dr. Zhaozhen Jiang | Computer Science | Best Research Article Award

Assistant Researcher | Naval Submarine Academy | China

Dr. Zhaozhen Jiang is a distinguished researcher at the Navy Submarine Academy in Qingdao, China, specializing in intelligent systems, maritime navigation, and dynamic target search. His research focuses on the development of advanced path-planning algorithms and neural network–based optimization techniques for complex maritime environments. He has published extensively and collaborated widely with researchers across multiple disciplines, reflecting a strong commitment to interdisciplinary innovation. His recent work on GBNN-based maritime dynamic target search demonstrates a focus on enhancing operational decision-making and situational awareness in challenging naval contexts. Through his research, he aims to advance autonomous maritime systems and contribute to safer, more efficient naval operations, while fostering technological progress with meaningful societal impact.

Citation Metrics (Scopus)

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Citations

37

Documents

15

h-index

4

Citations

Documents

h-index

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Featured Publications

Mohammed Alenazi | Computer Engineering | Best Researcher Award

Mr. Mohammed Alenazi | Computer Engineering | Best Researcher Award

Assistant Professor | University of Tabuk | Saudi Arabia

Mr. Mohammed M. Alenazi is an accomplished academic and researcher with expertise in electrical and electronics engineering, computer engineering, and artificial intelligence applications in energy-efficient networks. He earned his Ph.D. in Electrical and Electronics Engineering from the University of Leeds, UK (2018–2022), focusing on energy efficiency in AI-powered communication systems. Prior to this, he completed his M.Eng. in Computer Engineering at Florida Institute of Technology, USA (2016–2017), and a B.Eng. in Computer Engineering from University Sultan Bin Fahad (2007–2011), along with an Associate’s degree in Electrical/Electronics Equipment Installation and Repair from Tabuk College of Technology (2002–2004). Professionally, Mr. Alenazi began his career as a Senior Engineer at Saudi Telecom Company (2006–2011), where he gained practical experience in optical fiber networks, before transitioning to academia as a Teaching Assistant at Northern Border University (2012–2013) and later at the University of Tabuk, where he continues to serve since 2013, eventually advancing into an assistant professorship. His research interests include machine learning, IoT networks, energy optimization, and intelligent systems, with key contributions in developing models for energy-efficient ML-based service placement, neural network embedding in IoT, and intelligent sterilization systems, reflected in several IEEE and Scopus-indexed publications. In addition to publications, he has contributed innovative patents, such as systems for vehicle communication during accidents. His research skills encompass advanced AI modeling, simulation of communication networks, and interdisciplinary problem-solving in sustainable technologies. Mr. Alenazi is an active member of IEEE, AAAI (USA), AISB (UK), PMI, and the Saudi Council of Engineers, and he holds prestigious certifications including CCNA, CompTIA Security+ CE, and PMP. He has consistently demonstrated leadership in academia and professional communities, bridging industry and research while mentoring students. With a growing academic profile of 28 citations, 7 documents, and an h-index of 3, he is well-positioned for continued impact and recognition in his field.

Profiles: Google Scholar | Scopus | ORCID  | 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. 2020 22nd International Conference on Transparent Optical Networks (ICTON), 1–6. 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. Proceedings of the Twelfth ACM International Conference on Future Energy Systems. Cited by: 11

  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. 2021 IEEE 7th World Forum on Internet of Things (WF-IoT), 935–941. Cited by: 9

  4. Banga, A. S., Alenazi, M. M., Innab, N., Alohali, M., Alhomayani, F. M., Algarni, M. H., & others. (2024). Remote cardiac system monitoring using 6G-IoT communication and deep learning. Wireless Personal Communications, 136(1), 123–142. Cited by: 4

  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. 2022 IEEE International Mediterranean Conference on Communications and Networking (MeditCom). Cited by: 4