Assist Prof. Dr. Seung-Bo Lee | Computer Science | Best Researcher Award
Assist Prof. Dr. Seung-Bo, Lee, Keimyung University School of Medicine, South Korea
Assistant Professor Dr. Seung-Bo Lee from Keimyung University School of Medicine in South Korea excels in Computer Science, specializing in innovative research areas. His dedication to advancing knowledge is evident through his impactful contributions to the field. Dr. Lee’s research focuses on cutting-edge technologies, enhancing understanding in computational methodologies and artificial intelligence. As a recipient of the Best Researcher Award, he continues to inspire with his insightful publications and academic leadership. His commitment to excellence is underscored by his role in shaping future generations of computer scientists. 🎓💻🌟
PROFILE
EDUCATION
🧠🖥️ Prof. Dr. Seung-Bo Lee pursued his academic journey at Korea University in Seoul, Korea, specializing in Brain and Cognitive Engineering. He completed his Ph.D. from 2015 to 2020, following a Bachelor’s degree in Computer and Communication Engineering from 2009 to 2015. His research focuses on integrating cognitive science with engineering principles, exploring innovative ways to enhance brain-computer interfaces. Throughout his academic career, he has contributed significantly to the field, blending expertise in neuroscience and engineering to advance cognitive technologies. Prof. Dr. Lee’s dedication to interdisciplinary research underscores his commitment to advancing our understanding of brain function and its applications in technology.
EMPLOYMENT
👨🏫 Assist. Prof. Dr. Seung-Bo Lee brings a rich background to his role as Assistant Professor in the Department of Medical Informatics at Keimyung University School of Medicine. Prior to this, he served as a Research Professor at Seoul National University Hospital’s Office of Hospital Information, enhancing healthcare data management. His experience includes a tenure as a Senior Research Engineer at LG CNS, contributing to innovative tech solutions. Dr. Lee’s career spans from senior research roles to academia, where he continues to integrate medical informatics with practical industry insights, driving advancements in healthcare technology and data management.
SOCIETY ACTIVITIES
“Assist. Prof. Dr. Seung-Bo Lee has been an Academician at The Korean Society of Medical Informatics since February 2023. His expertise spans medical informatics, contributing significantly to research and education in the field. Dr. Lee’s work focuses on integrating technology with healthcare, enhancing patient care through innovative informatics solutions. As an Academician, he plays a crucial role in shaping the society’s direction and fostering collaboration among medical informatics professionals. His dedication to advancing healthcare through technology is marked by his active participation in conferences and publications. 🏥💻📚”
Awards and Honors
Dr. Seung-Bo Lee holds a Ph.D. in Brain and Cognitive Engineering from Korea University. As an accomplished researcher and academician, he has contributed significantly to the field of medical informatics. His work on predictive models using machine learning techniques has been published in renowned journals such as Scientific Reports and BMC Geriatrics. Dr. Lee’s dedication to advancing healthcare through technology is evident in his multiple publications focused on EEG signal analysis, predictive modeling for healthcare outcomes, and AI applications in medical diagnostics. He is recognized for his expertise in neural networks and machine learning methodologies applied to medical data.🏆
Research Projects
🧠Dr. Seung-Bo Lee earned his Ph.D. in Brain and Cognitive Engineering (2015-2020) and B.S. in Computer and Communication Engineering (2009-2015) from Korea University. Currently an Assistant Professor at Keimyung University School of Medicine, he previously served as a Research Professor at Seoul National University Hospital and Senior Research Engineer at LG CNS. Actively engaged in the Korean Society of Medical Informatics since 2023, his research spans predictive healthcare models using EEG and spirometry data, as published in high-impact journals. Lee’s contributions include machine learning applications in medical contexts, enhancing diagnostics and patient care.
Publication Top Notes
Classification of computed tomography scanner manufacturer using support vector machine
A machine learning approach for predicting suicidal ideation in post stroke patients