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.

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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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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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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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Mohamed Moncef Ben Khelifa | Computer Vision | Best Researcher Award

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Mr. Mohamed Moncef Ben Khelifa | Computer Vision | Best Researcher Award

Associate Professor | University of Toulon France | France

Dr. Mohamed Moncef Ben Khelifa, Maître de Conférences des Universités (HC, 61e CNU) au département MMI de l’IUT de Toulon et membre du laboratoire J-AP2S, est un spécialiste reconnu en vision assistée par ordinateur, intelligence artificielle appliquée à la santé, et interfaces intelligentes homme-machine, avec une expertise consolidée par plus de deux décennies d’enseignement, de recherche appliquée et d’innovation technologique. Titulaire d’une double compétence en traitement du signal et de l’image ainsi qu’en neurotechnologie, il a contribué à un ensemble significatif de travaux portant sur la biométrie, l’optimisation multi-objectifs, la classification d’images médicales, l’analyse prédictive de la marche et les interfaces cerveau-machine, totalisant de nombreuses publications indexées et plusieurs projets collaboratifs internationaux, notamment dans le cadre de coopérations scientifiques franco-tunisiennes. Ses travaux récents portent sur la classification biométrique avancée, l’optimisation par essaims intelligents, l’analyse markerless de la démarche pour la détection des pathologies musculosquelettiques, ainsi que sur la modélisation prédictive des troubles de la posture. En neuroergonomie et en cognition, il a proposé des approches intégrant signaux EEG, indices musculaires et paramètres oculaires afin de mesurer le stress, la fatigue mentale et la charge cognitive dans des environnements immersifs. Son engagement en mobilité assistée est également notable, illustré par ses recherches sur la navigation de fauteuils roulants via la fusion de données cérébrales et visuelles, ainsi que par ses innovations brevetées (France et États-Unis) dédiées au contrôle d’appareils mobiles. Lauréat du Prix Var Terre d’Innovation 2014 pour le projet BEWHEELI – Brain Eyes Wheelchair Interface, il œuvre pour la conception de technologies inclusives visant à améliorer l’autonomie des personnes à besoins spécifiques. Par son rôle de coordinateur de projets transméditerranéens, il contribue activement aux avancées en santé numérique pédiatrique, systèmes embarqués intelligents et traitement multimodal de données cliniques, renforçant l’impact sociétal de ses recherches au service de la santé publique et de l’innovation biomédicale.

Featured Publications

Abellard, A., & Ben Khelifa, M. M. (2004). A Petri net modelling of a neural human–machine interface. In IEEE International Conference on Industrial Technology (ICIT).

Abellard, A., Ben Khelifa, M. M., & Bouchouicha, M. (2005). A Petri net modelling of an adaptive learning control applied to an electric wheelchair. In Computational Intelligence in Robotics and Automation.

Abellard, A., Ben Khelifa, M. M., Bouchouicha, M., & Abellard, P. (2003). Modélisation par réseaux de Petri pour une programmation VHDL. Exemple d’application en robotique mobile d’assistance au handicap. ISDM Journal, 1–7.

Abellard, A., Randria, I., Franceschi, M., Abellard, P., & Ben Khelifa, M. M. (2018). Feasibility study of a technical programme for electric wheelchair steering aid.

Abellard, A., Randria, I., & Ben Khelifa, M. M. (2006). Utilisation des réseaux de Petri architecturaux pour la modélisation des algorithmes de commande d’une plateforme technologique d’aide aux handicapés. In SETIT 2005.

Dr. Ben Khelifa’s work bridges artificial intelligence, neurotechnologies, and predictive biomechanics to design inclusive solutions for healthcare and mobility assistance. His research drives innovation in pediatric digital health, assistive robotics, and multimodal clinical data analysis, improving quality of life for populations with specific needs.