Prof. Dr. Jen-Jie Chieh | Smart Sensing | Research Excellence Award

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Prof. Dr. Jen-Jie Chieh | Smart Sensing | Research Excellence Award

National Taiwan Normal University | Taiwan

Prof. Dr. Jen Jie Chieh is an established researcher at National Taiwan Normal University with a strong scholarly presence in interdisciplinary scientific research. With 89 publications, Chieh has accumulated 2,550 citations, reflecting sustained academic influence and research relevance. The author’s h-index of 28 indicates both productivity and consistent citation impact within the field. Chieh has demonstrated extensive scholarly collaboration, working with 188 co-authors, highlighting active engagement in international and multi-institutional research networks. The body of work contributes to advancing theoretical understanding and applied knowledge, supporting evidence-based innovation and academic development. Through widely cited publications, Chieh’s research has informed subsequent studies and fostered knowledge dissemination beyond institutional boundaries. The citation reach and collaborative breadth suggest meaningful social and academic impact, supporting the translation of research outcomes into educational, scientific, and societal contexts. Overall, Chieh’s profile reflects a mature, influential research trajectory with sustained global visibility.

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2550

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89

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28

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Top 5 Featured Publications

Jose Rosas-Bustos | Quantum Integrity | Excellence in Quantum Computing Award

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Mr. Jose Rosas-Bustos | Quantum Integrity | Excellence in Quantum Computing Award

University of Waterloo | Canada

Mr. Jose Rosas-Bustos is a researcher at the University of Waterloo specializing in quantum communication, quantum information processing, and cybersecurity. His work focuses on uncovering hidden vulnerabilities in quantum systems, leveraging principles such as Heisenberg’s uncertainty to expand attack vectors, reflecting a strong commitment to advancing secure quantum technologies. He has contributed to both academic and applied domains, authoring peer-reviewed publications and securing multiple patents (five granted and two applications) on cloudless computing infrastructures, demonstrating innovation in decentralized transaction management and system architecture. With a total of 2 citations, an h-index of 1, and collaborative research with co-inventors and co-authors, his work bridges theoretical quantum research with practical implementations, highlighting potential societal impacts in secure computing and data privacy. Mr. Rosas-Bustos’s research integrates fundamental science with technological applications, positioning him as an emerging contributor to global cybersecurity and quantum information fields.

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Obada Al-Khatib | Blockchain | Research Excellence Award

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Dr. Obada Al-Khatib | Blockchain | Research Excellence Award

University of Wollongong in Dubai | United Arab Emirates

Dr. Obada Al-Khatib is an academic researcher specializing in machine learning, deep learning, and explainable artificial intelligence (XAI), with a strong focus on environmental intelligence, smart systems, and safety-critical applications. His research addresses real-world challenges such as wildfire prediction, battery thermal runaway, intrusion detection in vehicular networks, and climate-driven risk modeling, emphasizing model interpretability and robustness under data imbalance. He has authored 42 peer-reviewed publications, accumulating 161 citations, and holds an h-index of 7, reflecting sustained scholarly impact. Dr. Al-Khatib actively collaborates with an extensive international research network, as evidenced by 81 co-authors, supporting interdisciplinary and cross-regional knowledge exchange. His recent open-access works contribute to societal resilience, environmental sustainability, and technological safety, particularly in the context of climate change and intelligent infrastructure. Collectively, his research demonstrates both methodological rigor and meaningful social and environmental impact at a global level.

Citation Metrics (Scopus)

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161

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42

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7

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Top 5 Featured Publications

Fatih Aslan | Object Detection | Research Excellence Award

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Mr. Fatih Aslan | Object Detection | Research Excellence Award

Sefine Shipyard | Turkey

Mr. Fatih Aslan is a researcher specializing in applied artificial intelligence, computer vision, and deep learning, with a particular focus on occupational safety and industrial applications. His work centers on developing real-time vision-based systems for safety monitoring in construction and shipyard environments. He is the author of one peer-reviewed journal article published in Applied Sciences, which presents a deep-learning-based approach for recognizing helmet-wearing personnel from a distance, contributing to automated safety compliance and risk reduction. His research integrates advanced neural network architectures with practical deployment considerations, bridging academic innovation and industry needs. Aslan collaborates with academic researchers and industry professionals, reflecting an interdisciplinary and application-driven research profile. The societal impact of his work lies in enhancing workplace safety, reducing accidents, and supporting digital transformation in high-risk industrial sectors. His research contributes to the global effort to apply AI technologies for sustainable and safer working environments.

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Xiang Chen | Vehicle Dynamics | Research Excellence Award

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Assoc. Prof. Dr. Xiang Chen | Vehicle Dynamics | Research Excellence Award

Nanjing University of Aeronautics and Astronautics | China

Assoc. Prof. Dr. Xiang Chen is an Associate Professor at the College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, China. His research expertise lies in vehicle dynamics and control, intelligent automotive systems, combustion and thermal engineering, and energy-efficient powertrain technologies. He has authored 43 peer-reviewed publications, receiving 694 citations with an h-index of 13, reflecting sustained academic impact. His work integrates advanced control methods, neural-network-based predictive control, electro-hydraulic steering systems, and swirl combustor flow and ignition characteristics, contributing to both theoretical modeling and experimental validation. Dr. Chen’s research outputs are published in leading international journals such as Applied Thermal Engineering, ISA Transactions, and Proceedings of the IMechE. He maintains extensive international and interdisciplinary collaborations, as evidenced by a broad co-author network. His research supports automotive safety, energy optimization, and low-emission propulsion technologies, offering tangible societal benefits for sustainable transportation and advanced mobility systems.

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694

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Kelum A.A. Gamage | Ethical AI | Research Excellence Award

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Prof. Dr. Kelum A.A. Gamage | Ethical AI | Research Excellence Award

University of Glasgow | United Kingdom

Prof. Dr. Kelum A.A. Gamage is a distinguished academic based at the University of Glasgow, United Kingdom, with recognized expertise in engineering, applied sciences, and interdisciplinary research addressing real-world challenges. He has made substantial scholarly contributions, with over 120 peer-reviewed publications indexed in Scopus, attracting more than 2,800 citations and an h-index of 24, reflecting both productivity and sustained research impact. His work spans fundamental research and applied innovation, often bridging academia and industry, and demonstrates strong international collaboration, as evidenced by a wide network of global co-authors. Prof. Gamage’s research has contributed to advancements with clear societal relevance, including technology development, system optimization, and solutions aligned with sustainability and public benefit. Through research leadership, mentorship, and collaboration, he continues to influence scientific progress and capacity building at a global level.

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2,832

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121

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24

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Top 5 Featured Publications

Muhammed Zekeriya Gündüz | Cybersecurity | Best Review Paper Award

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Assoc. Prof. Dr. Muhammed Zekeriya Gündüz | Cybersecurity | Best Review Paper Award

Assistant Professor |  Bingöl University | Turkey

Assoc. Prof. Dr. Muhammed Zekeriya Gündüz is an active researcher and academic professional with expertise spanning cybersecurity, software engineering, information systems, and artificial intelligence. His professional experience includes academic teaching, research supervision, and applied projects focused on improving software quality, digital security awareness, and ransomware analysis. His research interests emphasize secure software design, cyber threat mitigation, AI-supported information systems, and technology-driven educational solutions. He possesses strong research skills in data analysis, academic publishing, project development, interdisciplinary collaboration, and technology integration. His scholarly work has earned recognition through academic visibility, impactful citations, and contributions to high-quality journals and review studies. Overall, his work reflects consistent academic productivity, applied relevance, and growing influence within computer science and cybersecurity research domains. He has achieved 746 Citations 8Documents 4h-index.

 

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Featured Publications

Cyber-security on Smart Grid: Threats and Potential Solutions

– Elsevier, Computer Networks, 2020 (Top Cited)

Internet of Things (IoT): Evolution, Components and Application Fields

– Pamukkale University Journal of Engineering Sciences, 2018
Analysis of Cyber-Attacks on Smart Grid Applications

– International Conference on Artificial Intelligence and Data Processing, 2018
Analysis of Cyber-Attacks in IoT-Based Critical Infrastructures

– International Journal of Information Security Science, 2019

Fabien Thomas Brans | Digital Forensics | Research Excellence Award

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Dr. Fabien Thomas Brans | Digital Forensics | Research Excellence Award

PhD in Computer Science  | CRGN / LIRA  | France

Dr. Fabien THOMAS-BRANS is a researcher and practitioner in computer science and digital forensics with a strong focus on the processing, diagnosis, and repair of digital evidence within judicial and investigative contexts. His professional experience centers on forensic analysis of electronic devices, legal data extraction, and failure analysis, with active involvement in collaborative projects alongside academic and applied research institutions. His research interests include forensic science, data extraction methodologies, electronic diagnosis and repair, flash and MMC memory analysis, and CRBNE-related forensic interventions, reflecting an interdisciplinary approach that bridges computer science, mathematics, and security domains. His research skills encompass advanced digital forensics techniques, memory error correction, evidence recovery processes, failure analysis, and the development of specialized forensic procedures and training programs. He has contributed to peer-reviewed indexed journal publications and ongoing research articles, demonstrating consistent scholarly output and applied impact. In addition, his work includes collaboration with internationally recognized institutions, highlighting both academic rigor and practical relevance. His awards and honors are reflected through recognition in research excellence–oriented initiatives and professional affiliations within national forensic and cybersecurity organizations. Overall, his profile illustrates a balanced combination of applied forensic expertise, research innovation, and collaborative engagement, contributing meaningfully to advancements in digital evidence handling and forensic computing. He has achieved 12 Citations 3 Documents 2h-index.

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Yuan Xiaolin | Machine Learning | Editorial Board Member

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Dr. Yuan Xiaolin | Machine Learning | Editorial Board Member

Professor | Hefei Institute of Physical Sciences, Chinese Academy of Sciences | China

Xiao Lin Yuan is an Associate Professor at the Institute of Plasma Physics, Chinese Academy of Sciences, and an expert in fusion engineering systems, with particular specialization in vacuum pumping, fueling systems, and intelligent diagnostics for fusion devices. He earned a doctoral degree in Nuclear Science and Engineering, following comprehensive academic training that laid a strong foundation in plasma physics and large-scale scientific instrumentation. His professional experience includes long-term research and technical roles at a national fusion research institute, where he has contributed to the design, integration, and optimization of critical subsystems for advanced tokamak facilities, as well as participation in nationally and internationally funded collaborative projects. His research focuses on vacuum system design, leak detection technologies, molecular pump fault diagnosis, and the application of artificial intelligence methods such as support vector machines and deep learning models to enhance reliability and predictive maintenance in fusion devices. He has published extensively in leading peer-reviewed journals and international conference proceedings in the fields of fusion engineering, nuclear science, and vacuum technology, demonstrating both methodological rigor and practical impact. Through his sustained research output, project involvement, and academic leadership, he has earned professional recognition within the fusion research community and actively contributes to the advancement of intelligent control and diagnostic technologies for next-generation fusion systems.

Profile : ORCID

Featured Publications

Yuan, X.-L., Chen, Y., Hu, J.-S., et al. (2016). Development and implementation of flowing liquid lithium limiter control system for EAST. Fusion Engineering and Design, 112, 332–337.

Yuan, X.-L., Chen, Y., Hu, J.-S., et al. (2018). 10 Hz pellet injection control system integration for EAST. Fusion Engineering and Design, 126, 130–138.

Yuan, X.-L., Chen, Y., et al. (2018). Development and implementation of supersonic molecular beam injection for EAST tokamak. Fusion Engineering and Design, 134, 62–67.

Yuan, X.-L., Chen, Y., et al. (2023). A support vector machine framework for fault detection in molecular pump. Journal of Nuclear Science and Technology, 60, 72–82.

Zhou, Y., Jiang, M., Yuan, X.-L., et al. (2024). Fault prediction of molecular pump based on DE-Bi-LSTM. Fusion Science and Technology, 80, 1001–1011.