Rong Chen | Engineering | Research Excellence Award

Mr. Rong Chen | Engineering | Research Excellence Award

Senior Engineer | Zhejiang Sci-Tech University | China

Mr. Rong Chen is a researcher affiliated with Zhejiang Sci-Tech University, China, specializing in mechanical engineering, structural dynamics, and vibration analysis. With multiple peer-reviewed publications, Chen has contributed to advanced research in crack length prediction, degradation life modeling, and vibration reduction systems using both numerical and experimental approaches. His work focuses on enhancing the reliability and performance of engineering systems, particularly in marine and structural applications. Collaborating with a diverse group of researchers, Chen’s studies address critical challenges in predictive maintenance and system durability. His research holds strong societal and industrial relevance by supporting safer, more efficient mechanical systems and advancing modern engineering technologies.

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Featured Publications

Nazish Abid | Engineering | Research Excellence Award

Dr. Nazish Abid | Engineering | Research Excellence Award

Lecturer | University of Bahrain | Bahrain

Dr. Abid, Nazish is a researcher affiliated with the University of Bahrain, Zallaq, Bahrain, with expertise in social sciences, urban studies, and the analysis of public spaces. With 14 scholarly publications and 30 citations, the researcher has established a growing academic profile, reflected in an h-index of 3. Their work emphasizes the intersection of built environments and societal dynamics, including recent contributions on public open spaces in academic campuses. Actively engaged in collaborative research with international co-authors, Abid’s studies contribute to sustainable urban development and community well-being, demonstrating a commitment to addressing real-world societal challenges through evidence-based research.

Citation Metrics (Scopus)

30
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30

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14

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3

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Aleeza Adeel | Computer Science | Research Excellence Award

Mrs. Aleeza Adeel | Computer Science | Research Excellence Award

The University of Waikato | New Zealand

Mrs. Aleeza Adeel is a Ph.D. student at the School of Computing and Mathematical Sciences, University of Waikato, New Zealand, specializing in digital twin frameworks, sustainable energy systems, and user-centered computing solutions. Her research focuses on developing interoperable and scalable digital twin technologies to optimize energy system management, enhance operational efficiency, and support sustainable resource utilization. She has contributed to peer-reviewed publications, including a recent article in Energies on an interoperable user-centered digital twin framework, demonstrating her commitment to integrating advanced computational models with real-world energy systems. Aleeza collaborates with interdisciplinary researchers, including experts in energy management and computational modeling, to ensure her work addresses both technical rigor and societal relevance. Her research contributes to sustainable energy transitions by providing data-driven, user-centric solutions that improve system performance, reduce environmental impact, and support informed decision-making in complex energy infrastructures.

Profile: View ORCID Profile 

Featured Publication


An Interoperable User‑Centred Digital Twin Framework for Sustainable Energy System Management

– Adeel, A., Apperley, M., & Walmsley, T. G., Energies, 2026, 19(2), Article 333

Miroslaw Kozielski | Computer Science | Best Researcher Award

Mr. Miroslaw Kozielski | Computer Science | Best Researcher Award

Kazimierz Wielki University | Poland

Mr. Mirosław Kozielski is a researcher at Kazimierz Wielki University in Bydgoszcz, Poland, specializing in computer science, with a strong focus on natural language processing (NLP), industrial informatics, and Industry 4.0/5.0 technologies. His research addresses the use of intelligent language-based systems for automated industrial documentation, knowledge representation, and digital transformation in modern manufacturing environments. He has authored 7 peer-reviewed publications, which have accumulated 35 citations, and holds an h-index of 3, reflecting a focused and emerging academic impact. Dr. Kozielski collaborates with interdisciplinary teams, contributing to the integration of artificial intelligence with industrial and organizational processes. His work supports the development of efficient, human-centric, and sustainable industrial systems, with societal impact through improved documentation quality, enhanced knowledge accessibility, and the practical adoption of advanced AI-driven solutions in contemporary industrial ecosystems.

Citation Metrics (Scopus)

35
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35

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7

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3

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Christian Schachtner | Computer Science | Research Excellence Award

Prof. Dr. Christian Schachtner | Computer Science | Research Excellence Award

Professor of Business Informatics | RheinMain University of Applied Sciences | Germany

Dr. Christian Schachtner is a researcher at Fachhochschule Wiesbaden, Germany, specializing in safety culture, social impact assessment, and sustainable development in technical and organizational systems. His work bridges corporate social responsibility, environmental management, and smart district development, emphasizing practical solutions to complex societal challenges. According to Scopus, he has authored 23 scholarly publications, received 9 citations, and holds an h-index of 2. His recent research includes open-access work on the determinants of social impact through safety culture in technical organizations and scholarly contributions to book chapters on smart regional and district development initiatives. Dr. Schachtner actively collaborates with international researchers, supporting interdisciplinary perspectives and knowledge exchange. His research contributes to improving organizational governance, enhancing safety performance, and promoting socially responsible and sustainable practices across technical and socio-economic domains.

Citation Metrics (Scopus)

23
15
10
5
0

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9

Documents

23

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2

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h-index

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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)

40
30
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37

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15

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4

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Sarbajit Paul Bappy | Computer Science | Research Excellence Award

Mr. Sarbajit Paul Bappy | Computer Science | Research Excellence Award

Teaching Assistant | Daffodil International University | Bangladesh

Sarbajit Paul Bappy is an emerging researcher in computer science with a growing focus on applied machine learning, medical image analysis, and agricultural informatics. He is currently serving as a Teaching Assistant in the Department of Computer Science and Engineering at Daffodil International University, Bangladesh, where he has been contributing to academic instruction and research support since 2025. Alongside his professional role, he is pursuing his undergraduate degree in Computer Science and Engineering at the same institution, demonstrating a strong integration of academic excellence and early-career research productivity. His scholarly work includes peer-reviewed publications and openly accessible datasets that address critical challenges in healthcare diagnostics and smart agriculture. Notably, he co-authored SkinVisualNet: A Hybrid Deep Learning Approach Leveraging Explainable Models for Identifying Lyme Disease from Skin Rash Images (MAKE, 2025), which combines deep learning with explainable AI techniques to enhance early disease detection. He also contributed significantly to the dataset Jackfruit AgroVision, a comprehensive benchmark for disease detection in jackfruit and its leaves, supporting advancements in precision agriculture and food-security research. His collaborations span multidisciplinary teams involving experts such as Amir Sohel, Rittik Chandra Das Turjy, Md Assaduzzaman, Ahmed Al Marouf, Jon George Rokne, and Reda Alhajj, illustrating his ability to contribute within diverse international research groups. Through his ongoing work in AI-driven health diagnostics, dataset development, and sustainable agricultural technology, Bappy aims to advance research that supports societal well-being, improves disease detection accuracy, and contributes to innovation within global machine learning communities.

Profiles: Google Scholar | ORCID | LinkedIn

Featured Publications

1. Sohel, A., Turjy, R. C. D., Bappy, S. P., Assaduzzaman, M., Marouf, A. A., Rokne, J. G., & Alhajj, R. (2025). SkinVisualNet: A Hybrid Deep Learning Approach Leveraging Explainable Models for Identifying Lyme Disease from Skin Rash Images. Machine Learning and Knowledge Extraction, 7(4), 157. https://doi.org/10.3390/make7040157  MDPI+1

2. Sohel, A., Bijoy, M. H. I., Turjy, R. C. D., & Bappy, S. P. (2025). Jackfruit AgroVision: A Extensive Dataset for Jackfruit Disease and Leaf Disease Detection using Machine Learning. Mendeley Data. https://doi.org/10.17632/pt647jfn52.1

Jia Jinlong | Engineering | Research Excellence Award

Assoc. Prof. Dr. Jia Jinlong | Engineering | Research Excellence Award

Head of the Mining Department | Wuhan Institute of Technology | China

Dr. Jinlong Jia is a researcher at the Lanzhou Institute of Technology, China, specializing in coal engineering, gas extraction technologies, and energy-related geomechanics with a focus on improving safety, efficiency, and sustainability in coal mining operations. With 24 scientific publications, 434 citations, and an h-index of 12, he has established a strong research profile in the fields of coal pore structure evolution, borehole optimization, and fluid–rock interactions under complex geological conditions. His recent work includes developing numerical simulation models to quantitatively evaluate effect factors in multi-branch pinnate borehole gas extraction in high-gas thick coal seams, and investigating the influence of CO₂–H₂O interaction time on coal pore morphology and water migration, published in Energy and already earning citations for its contributions to clean energy and mine safety. Dr. Jia’s research integrates computational modeling, experimental coal chemistry, and engineering applications to address critical challenges in methane extraction, gas-solid coupling mechanisms, and geological hazard prevention. Over his career, he has collaborated with more than 67 co-authors, demonstrating extensive engagement in multidisciplinary and multi-institutional research teams working across geology, mining engineering, and energy science. His findings contribute to national and global efforts toward safer mining environments, enhanced gas utilization, reduced greenhouse gas emissions, and improved resource recovery efficiency. Through advancing both theoretical understanding and practical solutions in coalbed methane extraction and pore-scale mechanisms, Dr. Jia continues to play a significant role in supporting sustainable energy development and improving engineering practices within the mining and geoscience sectors.

Profile: Scopus 

Featured Publications

Zhu, X., Jia, J., Zhang, L., Ma, Z., Qin, Z., Zhang, H., & Liu, Z. (2025). Study on the numerical simulation model for quantitative evaluation on effect factors of multi‑branch pinnate borehole gas extraction in high‑gas thick coal seams. Himalayan Geology, 46(2), 125–135.

Xu, H., Hu, J., Liu, H., Ding, H., Zhang, K., Jia, J., Fang, H., & Gou, B. (2024). Effect of the interaction time of CO₂–H₂O on the alterations of coal pore morphologies and water migration during wetting. Energy, 294, Article 130944. https://doi.org/10.1016/j.energy.2024.130944

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

Mohamed Zakaria | Engineering | Best Researcher Award

Dr. Mohamed Zakaria | Engineering | Best Researcher Award

Kafrelsheikh University Faculty of Engineering, Egypt

Dr. Mohamed H. Zakaria, an Assistant Professor in Civil Engineering at Kafrelsheikh University, Egypt, is a dedicated researcher specializing in Soil Mechanics, Foundation Engineering, Highway Engineering, and Reinforced Concrete. With a Ph.D. from Menoufia University and a consistent academic trajectory, he has published extensively in reputable international journals, contributing innovative research on structural behavior, excavation systems, and the integration of advanced techniques such as machine learning and finite element modeling. His recent work addresses critical infrastructure challenges, reflecting both technical depth and practical relevance. Dr. Zakaria maintains active profiles on ORCID, Scopus, and ResearchGate, demonstrating his engagement with the global research community. His research reflects strong potential for collaboration and societal impact. While he could further enhance his profile through increased citations, international projects, and mentorship roles, his achievements and commitment make him a highly suitable candidate for the Best Researcher Award, with significant promise for future contributions.

Professional Profile 

Education🎓

Dr. Mohamed H. Zakaria has pursued a robust and progressive academic path in the field of Civil Engineering. He earned his Ph.D. in Civil Engineering from Menoufia University, Egypt, where he focused on advanced geotechnical and structural engineering concepts. Prior to this, he obtained a Master of Science degree in Civil Engineering from Kafrelsheikh University, further deepening his expertise in soil mechanics and foundation engineering. His academic journey began at Kafrelsheikh University, where he laid a strong foundation in engineering principles. Throughout his educational career, Dr. Zakaria demonstrated academic excellence, dedication to research, and a commitment to innovation. His studies have equipped him with both theoretical knowledge and practical problem-solving skills, which are evident in his applied research and numerous publications. His educational background not only reflects a high level of specialization in his chosen field but also positions him well for continued contributions to civil engineering education and research.

Professional Experience📝

Dr. Mohamed H. Zakaria has amassed extensive professional experience in the field of Civil Engineering, primarily through his longstanding association with Kafrelsheikh University in Egypt. He began his academic career as a Demonstrator in 2014, steadily progressing to the position of Assistant Lecturer in 2019, and currently serves as an Assistant Professor in the Civil Engineering Department. His roles have encompassed teaching, mentoring, and conducting impactful research in soil mechanics, foundation engineering, and highway engineering. Dr. Zakaria has contributed significantly to the academic community through his involvement in experimental investigations, numerical modeling, and structural analysis. His research has been published in numerous high-impact journals, reflecting both academic rigor and practical relevance. Through his professional journey, he has demonstrated a strong commitment to advancing civil engineering knowledge and fostering innovation. His experience positions him as a capable educator, active researcher, and a valuable contributor to both academic and applied engineering projects.

Research Interest🔎

Dr. Mohamed H. Zakaria’s research interests are rooted in the core areas of Civil Engineering, with a particular focus on Soil Mechanics, Foundation Engineering, Highway Engineering, and Reinforced Concrete. He is especially passionate about understanding and improving the behavior of structural systems under various loading and environmental conditions. His work explores critical challenges such as settlement mitigation, bearing capacity enhancement, and the structural performance of pile walls and reinforced concrete elements. Dr. Zakaria is also interested in the application of advanced techniques like finite element modeling, machine learning, and experimental methods to optimize design and construction practices. His interdisciplinary approach combines theoretical modeling with practical experimentation, aiming to develop innovative and sustainable engineering solutions. Through his research, he seeks to enhance the safety, durability, and efficiency of infrastructure systems, making a tangible impact on both academic knowledge and engineering practice. His work invites collaboration and has strong potential for global relevance.

Award and Honor🏆

Dr. Mohamed H. Zakaria has earned recognition for his dedication to research and academic excellence in Civil Engineering. While specific named awards and honors are not extensively listed in public records, his consistent publication of high-quality research in reputable, peer-reviewed international journals reflects his scholarly impact and recognition within the academic community. His achievements in developing innovative solutions for geotechnical and structural engineering challenges, such as enhancing the performance of secant pile walls and utilizing machine learning in structural prediction, demonstrate both technical expertise and thought leadership. His rising citation metrics and growing international research collaborations also highlight his influence and professional standing. Dr. Zakaria’s academic progression—from Demonstrator to Assistant Professor at Kafrelsheikh University—illustrates his merit and recognition by peers and institutions. As he continues to contribute significantly to his field, he is well-positioned to receive further honors and awards in acknowledgment of his impactful research and academic leadership.

Research Skill🔬

Dr. Mohamed H. Zakaria possesses a diverse and well-developed set of research skills that span both theoretical and practical aspects of Civil Engineering. He is highly proficient in experimental design and laboratory testing, particularly in the areas of soil mechanics, foundation behavior, and reinforced concrete structures. His ability to conduct complex analyses is complemented by his expertise in numerical modeling, including the use of finite element methods for simulating structural and geotechnical behavior. Additionally, Dr. Zakaria has demonstrated skill in applying advanced technologies such as machine learning to predict structural performance, showcasing his adaptability and innovation in solving engineering problems. He is also adept at conducting comprehensive literature reviews, synthesizing technical data, and publishing findings in high-impact journals. His collaborative approach and strong communication skills enhance his ability to work across multidisciplinary teams. Overall, his research skillset makes him a valuable contributor to academic advancements and practical engineering solutions.

Conclusion💡

Dr. Mohamed H. Zakaria is a highly promising and dedicated researcher with a strong and focused track record in civil engineering. His steady academic career, continuous publication record, and exploration of advanced methods like machine learning and FE modeling in civil applications showcase technical excellence and innovative thinking.

Publications Top Noted✍️

  1. Title: Mitigating Settlement and Enhancing Bearing Capacity of Adjacent Strip Footings Using Sheet Pile Walls: An Experimental Approach
    Authors: Ali Basha, Ahmed Yousry Akal, Mohamed H. Zakaria
    Year: 2025
    Citation: Infrastructures, 2025, DOI: 10.3390/infrastructures10040083

  2. Title: A Comparative Study of Terrestrial Laser Scanning and Photogrammetry: Accuracy and Applications
    Authors: Mohamed H. Zakaria, Hossam Fawzy, Mohammed El-Beshbeshy, Magda Farhan
    Year: 2025
    Citation: Civil Engineering Journal, March 2025, DOI: 10.28991/cej-2025-011-03-021

  3. Title: Cantilever Piled-Wall Design Criteria in Cohesionless Soil: A Review
    Authors: Mohamed Hamed Zakaria, Ali Basha
    Year: 2024
    Citation: World Journal of Engineering, 2024, DOI: 10.1108/WJE-01-2024-0038

  4. Title: Prediction of RC T-Beams Shear Strength Based on Machine Learning
    Authors: Saad A. Yehia, Sabry Fayed, Mohamed H. Zakaria, Ramy I. Shahin
    Year: 2024
    Citation: International Journal of Concrete Structures and Materials, 2024, DOI: 10.1186/S40069-024-00690-Z

  5. Title: Effect of Insufficient Tension Lap Splices on the Deformability and Crack Resistance of Reinforced Concrete Beams: A Comparative Study Techniques and Experimental Study
    Authors: Roba Osman, Boshra El-taly, Ahmed Fahmy, Mohamed Zakaria
    Year: 2024
    Citation: Engineering Research Journal, Nov 2024, DOI: 10.21608/erjm.2024.296635.1337

  6. Title: Predicting the Maximum Axial Capacity of Secant Pile Walls Embedded in Sandy Soil
    Authors: Ali M. Basha, Mohamed H. Zakaria, Maher T. El-Nimr, Mohamed M. Abo-Raya
    Year: 2024
    Citation: Geotechnical and Geological Engineering, July 2024, DOI: 10.1007/s10706-023-02734-9

  7. Title: Two-Dimensional Numerical Approaches of Excavation Support Systems: A Comprehensive Review of Key Considerations and Modelling Techniques
    Authors: Mohamed Hamed Zakaria, Ali Basha
    Year: 2024
    Citation: Journal of Contemporary Technology and Applied Engineering, July 2024, DOI: 10.21608/jctae.2024.299692.1030

  8. Title: Interfacial Shear Behavior of Composite Concrete Substrate to High-Performance Concrete Overly After Exposure to Elevated Temperature
    Authors: Nagat M. Zalhaf, Sabry Fayed, Mohamed H. Zakaria
    Year: 2024
    Citation: International Journal of Concrete Structures and Materials, March 2024, DOI: 10.1186/s40069-023-00654-9