Wasiu Akande Ahmed | Artificial Intelligence in Diagnostics | Research Excellence Award

Assist. Prof. Dr. Wasiu Akande Ahmed | Artificial Intelligence in Diagnostics | Research Excellence Award

Assistant Professor | Hangzhou International Innovation Institute of Beihang University | China

Dr. Wasiu Akande Ahmed is an accomplished researcher whose work centers on advanced challenges in global navigation satellite systems (GNSS), satellite communication, and space-based sensing technologies. His research portfolio spans GNSS signal processing, multipath and interference mitigation, signal delay modeling, and noise reduction, with significant contributions to AI-enhanced error correction and system optimization. He is widely recognized for pioneering studies in GNSS reflectometry for environmental monitoring and GNSS-based weather forecasting using radio occultation techniques. His interdisciplinary research further extends to UAV-enabled applications, precision agriculture, climate-smart farming, food security, and 5G–GNSS integration for next-generation location-based services. With numerous publications in high-impact journals and international conferences, multiple patents, and authorship of scholarly books and chapters, his work demonstrates strong translational potential. Through collaborative and innovative research, he continues to advance the frontiers of satellite navigation, remote sensing, and resilient positioning technologies.

Citation Metrics (ResearchGate)

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51
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26
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Anastasios Koulaouzidis | Artificial Intelligence in Diagnostics | Research Excellence Award

Prof. Dr. Anastasios Koulaouzidis | Artificial Intelligence in Diagnostics | Research Excellence Award

Clinical Professor | University of Southern Denmark | Denmark

Dr. Anastasios Koulaouzidis is an internationally recognized researcher in gastroenterology with a primary focus on capsule endoscopy, minimally invasive gastrointestinal diagnostics, and the clinical integration of artificial intelligence in endoscopic practice. His scholarly work has significantly shaped quality metrics, consensus guidelines, and real-world implementation strategies for small-bowel and colon capsule endoscopy across Europe and beyond. He has authored 352 peer-reviewed scientific documents, encompassing original research, systematic reviews, meta-analyses, consensus statements, and guideline contributions, reflecting sustained productivity and leadership in translational and clinical research. His publications have collectively attracted 7,744 citations, underscoring their broad scientific influence and adoption within the global gastroenterology community, and he holds an h-index of 49, indicating consistent high-impact output over time. His research portfolio bridges diagnostic innovation, health-care efficiency, and patient-centered outcomes, with particular emphasis on quality improvement, standardization, and future-ready technologies in gastrointestinal endoscopy.

Citation Metrics (Scopus)

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7,744
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352
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49
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Xiangli Li | Artificial Intelligence in Diagnostics | Excellence in Research Award

Dr. Xiangli Li | Artificial Intelligence in Diagnostics | Excellence in Research Award

Doctoral Student | Wuhan University | China

Dr. Xiangli Li is a research-focused scientist specializing in artificial intelligence–driven medical image analysis and multimodal clinical data interpretation. The research portfolio comprises 26 citations, an h-index of 3, and 8 peer-reviewed research documents published in indexed journals and conference proceedings. Scholarly work emphasizes deep learning, computer vision, and multimodal neural network architectures applied to diagnostic pathology, with particular impact in thyroid cytology classification and decision-support systems. Publications demonstrate consistent contributions to translational medical AI, advancing accuracy, robustness, and clinical relevance of computational models. The research output reflects steady citation growth, interdisciplinary relevance, and measurable scientific influence within medical informatics and applied artificial intelligence. Collectively, these works contribute to evidence-based diagnostic innovation, strengthening the integration of advanced AI methodologies into modern biomedical research and clinical practice.

Citation Metrics (Scopus)

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26
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8
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3
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Featured Publications

Helala AlShehri | Artificial Intelligence in Diagnostics | Research Excellence Award

Prof. Helala AlShehri | Artificial Intelligence in Diagnostics | Research Excellence Award

Assistant Professor | Jubail Industrial College | Saudi Arabia

Prof. Helala Mohammad AlShehri is a research-focused scholar in computer science whose work centers on artificial intelligence, deep learning, and data-driven methodologies with applications in medical imaging and intelligent systems. The research portfolio comprises 6 peer-reviewed documents published in reputable indexed journals, reflecting sustained contributions to methodological development and applied AI research. These works have collectively received 97 scholarly citations, demonstrating measurable academic impact and visibility within the research community. With an h-index of 5, the body of work indicates consistent citation performance across multiple publications, highlighting both productivity and influence. The research emphasizes model robustness, interpretability, and performance optimization, particularly in pattern recognition, image analysis, and computational intelligence. Through interdisciplinary collaboration and rigorous experimental validation, the contributions advance the integration of AI techniques into real-world analytical and diagnostic frameworks. Overall, the scholarly output reflects a focused, impact-oriented research trajectory supported by recognized citation metrics and peer-reviewed dissemination.

Citation Metrics (Scopus)

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97
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6
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5
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Featured Publications