Marwan | AI Advancements | Excellence in Research

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).

 

Bao Liu | Emerging Technologies | Best Researcher Award

Dr. Bao Liu | Emerging Technologies | Best Researcher Award

Dr. Bao Liu | Xi’an University of Science and Technology | China

Dr. Liu Bao is an Associate Professor and Academic Leader in the field of Pattern Recognition and Intelligent Systems at the School of Electrical and Control Engineering, Xi’an University of Science and Technology, where he also serves as a Graduate Supervisor and Project-based Ph.D. Supervisor. He earned his doctorate in engineering from Xi’an Jiaotong University, completed postdoctoral research at Xi’an University of Science and Technology, and broadened his academic experience as a visiting fellow at Macquarie University in Australia. Recognized as a Senior Data Analyst by the Ministry of Industry and Information Technology of China, Dr. Liu is an active member of several national academic societies and professional committees. His research focuses on multi-source information fusion and intelligent technologies for coal fire disaster prevention and control, integrating advanced computational and automation techniques to address complex industrial challenges. Throughout his career, he has led diverse national, provincial, and industry-based research projects and contributed extensively to scientific publications and technological innovation through patents and software developments. As a committed educator and mentor, Dr. Liu has inspired students to excel in academic and professional pursuits and has been honored with multiple awards recognizing his dedication to teaching, research, and academic service.

Profile: Orcid

Featured Publications

Liu, B., Liu, Q., & Wu, Z. (2026, February). A novel robust Student’s t scale mixture distribution based Kalman filter. Signal Processing. https://doi.org/10.1016/j.sigpro.2025.110296

Liu, B., Wu, Z., & Liu, Q. (2025). Gaussian mixture model-based variational Bayesian approach for extended target tracking. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2025.3565347

Liu, B., & Jiang, W. (2024). DFKD: Dynamic focused knowledge distillation approach for insulator defect detection. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2024.3485446

Liu, B., & Jiang, W. (2024, December). LA-YOLO: Bidirectional adaptive feature fusion approach for small object detection of insulator self-explosion defects. IEEE Transactions on Power Delivery. https://doi.org/10.1109/TPWRD.2024.3467915

Liu, B., Zhou, N., & Wang, Z. (2024, December 27). DFI-YOLOv8 based defect detection method for fan blades. In Proceedings of the 2024 Conference on [Insert Conference Name]. https://doi.org/10.1145/3722405.3722437