Marwan | AI Advancements | Excellence in Research

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Dr. Marwan | AI Advancements | Excellence in Research

Dr. Marwan | King Faisal University | Saudi Arabia

The applicant is an accomplished scholar in Computer Information Systems with specialized expertise in Artificial Intelligence and Data Science, supported by extensive experience in academia, research, and innovation. Over more than a decade of university-level teaching and research, the applicant has contributed significantly to advancing intelligent systems, machine learning applications, IoT security, biomedical imaging, and pattern recognition. Their doctoral work introduced a novel model for Arabic handwritten text recognition, forming the foundation for a strong research career in AI-driven language and image processing technologies. The applicant has authored and co-authored numerous impactful, refereed journal publications in well-recognized international outlets such as Sustainability, IJACSA, Traitement du Signal, and the Journal of Ayub Medical College. Research contributions span cancer therapy enhancement, anomaly detection, cephalometric landmark detection, multiple sclerosis classification, industrial IoT security, biometric iris recognition, palm disease classification, and Arabic word recognition. Several works have been indexed in Scopus and other reputable databases, with active collaborations involving interdisciplinary and multinational research teams. Beyond publications, the applicant has secured competitive research funding, including a grant supporting the development of a weighted-voting IoT security model targeting BASHLITE and Mirai cyberattacks. Ongoing research activities include hybrid deep learning systems for intrusion detection, medical image analysis, human nail disease diagnosis, music-brain interactions, and predicate-logic-based machine translation. The applicant has demonstrated strong academic service through extensive peer-reviewing, participation in scientific councils, and membership in research committees. Their professional development includes participation in conferences, training programs, and workshops focused on e-learning, scientific publishing, and advanced teaching strategies. Recognized for excellence, the applicant has received awards such as the Distinguished Scientific Research Award and the Outstanding International Publishing Award, reflecting sustained research quality and global scholarly impact. Their overall portfolio showcases a balanced blend of innovative research, academic leadership, and contributions to the AI and data science community.

Profiles: Scopus 

Featured Publications

Siddiqi, M. H., Alhwaiti, Y., Elaiwat, S., & Abu-Zanona, M. (2024). Dynamic healing process analysis: Image morphing with warping technique for nose and esophagus studies. The International Arab Journal of Information Technology, 21(3). (Accepted December 26, 2023).

 

Barham Farraj | Robotics Engineering | Best Researcher Award

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Mr. Barham Farraj | Robotics Engineering | Best Researcher Award

Mr. Barham Farraj | kromberg & schubert | Slovakia 

The researcher is a highly motivated and results-oriented Service and Development Engineer specializing in robotics, LiDAR systems, and autonomous driving technologies. His work focuses on bridging the gap between development and practical deployment of intelligent robotic systems, with a strong emphasis on perception, mapping, and navigation using LiDAR-based solutions. He has demonstrated exceptional technical expertise through hands-on experience at the Vehicle Research Center in Győr, Hungary, contributing significantly to autonomous vehicle research, system integration, and performance optimization. A key highlight of his research is the development of a real-time LiDAR-based urban road and sidewalk detection system for autonomous vehicles. This project integrates advanced LiDAR sensing with ROS2, C++, Python, and MATLAB, enabling robust environmental perception and accurate object classification in complex urban settings. By leveraging point cloud processing and machine learning techniques, his work enhances vehicle awareness, paving the way for safer and more efficient autonomous navigation. He has also contributed to major academic and industrial initiatives, including building and programming autonomous racing vehicles for international competitions such as RoboRacer and F1TENTH, and leading simulation-based testing in Gazebo and Foxglove environments. His research extends to transforming ROS1-based algorithms into ROS2 for improved modularity and scalability across multi-vehicle systems. In his current role at Kromberg & Schubert Automotive, Slovakia, he develops embedded applications and perception systems for industrial mobile platforms, integrating sensor data and diagnostics for enhanced reliability. His teaching and mentoring roles at Széchenyi István University reflect his dedication to knowledge transfer and educational impact in autonomous robotics. Through his combined research, engineering practice, and leadership, he has contributed to advancing LiDAR-driven perception, real-time mapping, and autonomous vehicle intelligence, marking him as a promising innovator in the field of intelligent mobility and robotic automation.

Profiles: Orcid

Featured Publications 

Barham Farraj, B. J., Alabdallah, A., Unger, M., & Horváth, E. (2025, October 31). Enhancing autonomous navigation: Real-time LiDAR detection of roads and sidewalks in ROS 2. Engineering Proceedings, 113(24). https://doi.org/10.3390/engproc2025113024

Krecht, R., Alabdallah, A. M. A., & Barham Farraj, B. J. (2025, October 28). Evaluation of SLAM methods for small-scale autonomous racing vehicles. Engineering Proceedings, 113(9). https://doi.org/10.3390/engproc2025113009

Alabdallah, A., Barham Farraj, B. J., & Horváth, E. (2025, October 28). ROS 2-based framework for semi-automatic vector map creation in autonomous driving systems. Engineering Proceedings, 113(13). https://doi.org/10.3390/engproc2025113013

Samia ZAOUI | AI Advancements | Women Researcher Award

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Mrs. Samia ZAOUI | AI Advancements | Women Researcher Award

Mrs. Samia ZAOUI | Mohammed VI Foundation of Health and Sciences | Morocco

Dr. Samia Zaoui, based in Rabat, Morocco, is a multidisciplinary researcher and project leader bridging artificial intelligence, aeronautics, and healthcare systems innovation. She is currently pursuing her Ph.D. in Computer Science Engineering (AI & Aeronautics) at the Higher Institute of Aeronautics and Space (ISAE-SUPAERO) and INP Toulouse, France. Her research focuses on the application of AI technologies for supply chain resilience, predictive modeling, and sustainable industrial systems, with a strong emphasis on pharmaceutical and healthcare logistics. Dr. Zaoui has an extensive background in strategic project development, digital transformation, and industrial management, having held leadership roles at the Mohammed VI Foundation of Health and Sciences and the Cheikh Zaid Foundation. She has spearheaded projects in sports medicine innovation, pharmaceutical manufacturing, and medical technology transfer, fostering collaborations with international organizations such as WHO, LCIF, and Smile Train. Her scientific contributions include several peer-reviewed publications in international journals, such as the Global Journal of Flexible Systems Management and Production Planning & Control, covering topics like AI-driven supply chain viability, sustainability in Industry 5.0, and pharmaceutical risk prediction using machine learning. Dr. Zaoui’s research integrates AI-based decision systems with aeronautical and industrial engineering principles, contributing to global efforts in intelligent, resilient, and sustainable supply networks. She also actively participates in international technology exhibitions and collaborative industrial initiatives across Europe, Asia, and Africa.

Profile: Google Scholar

Featured Publications

Zaoui, S., Foguem, C., Tchuente, D., Fosso-Wamba, S., & Kamsu-Foguem, B. (2023). The viability of supply chains with interpretable learning systems: The case of COVID-19 vaccine deliveries. Global Journal of Flexible Systems Management, 24(4), 633–657. https://doi.org/10.1007/s40171-023-00357-w

Zaoui, S., Foguem, C., Tchuente, D., & Kamsu-Foguem, B. (2025). The application of artificial intelligence technologies in the resilience and the viability of supply chains: A systematic literature review. Production Planning & Control, 1–18.

Zaoui, H., Zaoui, S., Kamsu-Foguem, B., & Tchuente, D. (2024). Sustainability: The main pillar of Industry 5.0. Oklahoma International Publishing (OkIP) Books. https://doi.org/10.55432/978-1-6692-0007-9_13

StEER – Structural Engineering Extreme Event Reconnaissance. (2024). Hualien City, Taiwan Earthquake: Preliminary Virtual Reconnaissance Report (PVRR). https://doi.org/10.17603/ds2-0d2z-9682

Keyi Chen | AI Advancements | Best Researcher Award

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Mr. Keyi Chen Jihua Laboratory | AI Advancements | Best Researcher Award

Mr. Keyi Chen | Jihua Laboratory | China

Keyi Chen is a dedicated research engineer at Jihua Laboratory, Foshan, Guangdong Province, China. He obtained his MSc in Crop Informatics from Huazhong Agricultural University , where he built a strong foundation in computational modeling and artificial intelligence applications. His research primarily focuses on deep learning algorithms, particularly their integration into computer-based recognition systems and intelligent environmental analysis. He has completed three research projects and participated in one industry consultancy project, demonstrating both academic and applied innovation. His current research explores AI-driven recognition of marine microalgae, an essential area for assessing aquatic ecological health. In this domain, Chen developed a ResNeXt-50-based multi-expert network with an exponential feature compression mechanism that effectively mitigates class imbalance issues. Evaluated on the WHIO-Plankton dataset, his model achieved a state-of-the-art performance with an average precision and average recall , outperforming existing baselines. The system’s low inference latency demonstrates high real-time feasibility. His contributions provide a robust framework for marine microalgae recognition, supporting environmental monitoring and marine life science research. With Citations by 38 documents, 3 publications, and an h-index of 2, Chen has established himself as a rising researcher in applied AI and computational biology. His ongoing innovations signify impactful potential in environmental intelligence, sustainable technology, and bioinformatics applications.

Profile: Scopus | Orcid

Featured Publications

Chen, K., Cui, S., Zhong, J., & Wang, Q. (2025). MicroalgaeNet: Enhancing recognition of long-tailed marine microalgae images through multi-expert networks and feature compression. Algal Research, 92, 104333. https://doi.org/10.1016/j.algal.2025.104333

Song, P., Chen, K., Zhu, L., Yang, M., Ji, C., Xiao, A., Jia, H., Zhang, J., & Yang, W. (2022). An improved cascade R-CNN and RGB-D camera-based method for dynamic cotton top bud recognition and localization in the field. Computers and Electronics in Agriculture, 202, 107442. https://doi.org/10.1016/j.compag.2022.107442