
Mohammed A. Al-masni
Assistant Professor · Medical Image Analysis
University of Hawaiʻi at MānoaAbout
Mohammed A. Al-masni is currently serving as an Assistant Professor in the Department of Artificial Intelligence at Sejong University, Seoul, Republic of Korea, a position he has held since September 2022. Prior to this appointment, he worked as a Research Professor at Yonsei University (November 2020-August 2022) and as a Postdoctoral Researcher at the same institution (September 2019-October 2020). His academic journey includes significant research experience in medical imaging and artificial intelligence applications in healthcare.
His educational background includes:
- Bachelor's Degree from Cairo University, Egypt (June 2011)
- M.Sc. from Cairo University, Egypt (February 2015)
- Ph.D. in Biomedical Engineering from Kyung Hee University, Republic of Korea (August 2019)
Dr. Al-masni's research focuses at the intersection of artificial intelligence and medical imaging. His primary areas of investigation include medical image analysis, deep learning applications for medical diagnostics, and computer-aided diagnosis systems. He has developed innovative approaches for addressing motion artifacts in MRI, cerebral microbleed detection, and skin lesion segmentation. His work demonstrates a consistent pattern of applying cutting-edge deep learning techniques to solve challenging problems in medical imaging, with particular emphasis on improving diagnostic accuracy and efficiency.
Analysis of his recent publications reveals a strong focus on medical image processing challenges, particularly in MRI and dermoscopy applications. His research demonstrates an evolution from basic image segmentation techniques to more sophisticated multi-task learning frameworks that address multiple clinical challenges simultaneously. A significant portion of his work targets neurological imaging applications, including cerebral microbleed detection and motion artifact correction in brain MRI. More recently, his research has expanded to include cross-domain applications of deep learning in software engineering and environmental monitoring.
While specific awards are not explicitly listed in the provided information, his research impact is evidenced by an h-index of 17 and 2,313 citations according to Scopus metrics. His work contributes to UN Sustainable Development Goals, particularly in the area of good health and well-being.
Dr. Al-masni has been actively involved in research collaborations, primarily with Dong-Hyun Kim's Lab at Yonsei University. His research output shows consistent productivity with 57 research outputs documented, including numerous high-impact journal articles in medical imaging and AI venues. His work demonstrates strong industry and academic collaboration, particularly in the development of practical diagnostic tools for clinical applications.
His laboratory work has centered around medical imaging applications, with particular focus on the development of deep learning frameworks for medical image analysis. His research group appears to be focused on creating robust, clinically applicable AI tools that can address real-world challenges in medical diagnostics, with emphasis on neurological disorders and skin cancer detection.
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