Assistant Professor at University of Ulsan, South Korea
Dr. Seho Lee, Assistant Professor in the Department of AI Convergence, is a distinguished researcher specializing in neuroengineering, brain–computer interfaces (BCI), and clinical artificial intelligence. He earned his Ph.D. in Brain and Cognitive Engineering from Korea University, following advanced degrees in biomedical engineering and electrophysics. His research focuses on advanced neurophysiological signal analysis, AI-based clinical decision support, and predictive modeling for neurological disorders. Dr. Lee has played key roles in multiple international, grant-funded projects and has published extensively in high-impact journals, including IEEE and Frontiers in Neuroscience. Holding several patents in BCI and biomedical AI, he is also an active member of professional bodies like IEEE. With a strong commitment to innovation, interdisciplinary collaboration, and mentorship, Dr. Lee continues to advance technologies that bridge engineering and clinical applications for global impact.
Professional Profile
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Education
Dr. Seho Lee holds a Ph.D. in Brain and Cognitive Engineering from Korea University, where he specialized in advanced neurophysiological signal processing and AI applications in neuroscience. He earned his Master’s degree in Biomedical Engineering from Hanyang University, focusing on biomedical signal analysis and neural interface technologies. His academic journey began with a Bachelor’s degree in Electrophysics from Kwangwoon University, where he developed a strong foundation in physics and electronics. This diverse educational background has enabled Dr. Lee to integrate engineering, computer science, and neuroscience in his research. His training at leading Korean institutions provided both theoretical depth and practical expertise, positioning him to contribute meaningfully to the rapidly evolving fields of neuroengineering, artificial intelligence, and clinical technology innovation at both national and global levels.
Experience
Dr. Lee currently serves as an Assistant Professor in the Department of AI Convergence, where he leads research at the intersection of neuroscience, artificial intelligence, and clinical applications. He has been a key contributor to multiple multi-year, grant-funded projects, collaborating with hospitals, research institutes, and industry partners. His work spans developing brain–computer interface (BCI) systems, AI-powered clinical decision support tools, and predictive models for neurological disorder progression. Dr. Lee’s experience includes managing large datasets, integrating wearable and invasive neural monitoring technologies, and designing patient-centric solutions. His portfolio also features active involvement in interdisciplinary teams, student supervision, and community-driven scientific initiatives. Through his extensive project work and academic contributions, he has developed a global research perspective while ensuring his innovations address practical, real-world needs in healthcare and rehabilitation technologies.
Research Interest
Dr. Lee’s research interests focus on neuroengineering, brain–computer interfaces (BCI), clinical artificial intelligence, and neuroscience applications for patient rehabilitation. He specializes in advanced analysis of continuously measured neurophysiological signals, quantitative brain network modeling, and AI-driven diagnostic tools. His work aims to create practical solutions for individuals with neurological impairments by enhancing brain–machine communication and predictive clinical analytics. Key topics include the use of AI for clinical data interpretation, development of real-time decision support systems, and non-invasive neural stimulation methods. Dr. Lee is also deeply engaged in studying pathological progression in neurological disorders, with the goal of early intervention. His multidisciplinary approach combines engineering, cognitive science, and medicine, contributing to breakthroughs that directly improve patient quality of life and expand the capabilities of modern neurotechnology.
Award and Honor
While building his academic career, Dr. Lee has earned recognition through successful participation in competitive, nationally funded research projects and prestigious institutional appointments. His innovations in brain–computer interface technology and AI-based biomedical systems have resulted in multiple patents in Korea and the United States, marking him as a thought leader in his domain. He has been invited to present at leading IEEE conferences, demonstrating peer acknowledgment of his contributions. His publications in high-impact journals further attest to his research excellence. The combination of competitive grant awards, impactful publications, and translational research outcomes underscores Dr. Lee’s professional standing. These achievements not only highlight his expertise but also his commitment to advancing science with tangible applications, making him a strong candidate for distinguished research recognitions and honors.
Research Skill
Dr. Lee possesses a comprehensive set of research skills spanning AI model development, neurophysiological data acquisition and analysis, brain network modeling, and clinical signal interpretation. He is adept in programming, machine learning, and deep learning techniques applied to healthcare data, including EEG, EMG, and imaging modalities. His expertise extends to designing and implementing both hardware and software components for brain–computer interfaces, ensuring reliability and usability in clinical environments. Dr. Lee is skilled in statistical modeling, biomedical signal preprocessing, and data visualization for translational research. He has extensive experience collaborating across disciplines, managing international research collaborations, and guiding graduate students in advanced projects. Combined with his patent-proven innovation capabilities, these skills enable him to transform theoretical concepts into impactful neuroengineering solutions that address pressing healthcare challenges.
Publication Top Notes
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Title: Improved prediction of bimanual movements by a two-staged (effector-then-trajectory) decoder with epidural ECoG in nonhuman primates
Authors: H Choi, J Lee, J Park, S Lee, K Ahn, IY Kim, KM Lee, DP Jang
Year: 2018
Citations: 26
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Title: Physicochemical factors that affect electroporation of lung cancer and normal cell lines
Authors: HB Kim, S Lee, Y Shen, PD Ryu, Y Lee, JH Chung, CK Sung, KY Baik
Year: 2019
Citations: 24
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Title: Effects of actin cytoskeleton disruption on electroporation in vitro
Authors: HB Kim, S Lee, JH Chung, SN Kim, CK Sung, KY Baik
Year: 2020
Citations: 19
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Title: Importance of reliable EEG data in motor imagery classification: Attention level-based approach
Authors: S Lee, YT Kim, SO Hwang, H Kim, DJ Kim
Year: 2020
Citations: 7
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Title: Long-term evaluation and feasibility study of the insulated screw electrode for ECoG recording
Authors: H Choi, S Lee, J Lee, K Min, S Lim, J Park, K Ahn, IY Kim, KM Lee
Year: 2018
Citations: 6
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Title: Decoding saccadic directions using epidural ECoG in non-human primates
Authors: J Lee, H Choi, S Lee, BH Cho, K Ahn, IY Kim, KM Lee, DP Jang
Year: 2017
Citations: 6
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Title: Reduced burden of individual calibration process in brain–computer interface by clustering the subjects based on brain activation
Authors: YT Kim, S Lee, H Kim, SB Lee, SW Lee, DJ Kim
Year: 2019
Citations: 4
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Title: Right hemisphere lateralization in neural connectivity within fronto-parietal networks in non-human primates during a visual reaching task
Authors: J Lee, H Choi, K Min, S Lee, KH Ahn, HJ Jo, IY Kim, DP Jang, KM Lee
Year: 2018
Citations: 3
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Title: Investigating the effect of mindfulness training for stress management in military training: the relationship between the autonomic nervous system and emotional regulation
Authors: S Lee, JH Kim, H Kim, SH Kim, SS Park, CW Hong, KT Kwon, SH Lee
Year: 2025
Citations: 2
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Title: Effects of altered functional connectivity on motor imagery brain–computer interfaces based on the laterality of paralysis in hemiplegia patients
Authors: S Lee, H Kim, JB Kim, DJ Kim
Year: 2023
Citations: 2
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Title: Classification of the motion artifacts in near-infrared spectroscopy based on wavelet statistical feature
Authors: SB Lee, H Kim, S Lee, HJ Kim, SW Lee, DJ Kim
Year: 2019
Citations: 2
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Title: Heart rate variability as a preictal marker for determining the laterality of seizure onset zone in frontal lobe epilepsy
Authors: S Lee, H Kim, JH Kim, M So, JB Kim, DJ Kim
Year: 2024
Conclusion
Dr. Seho Lee represents the next generation of innovators at the convergence of neuroscience, artificial intelligence, and clinical technology. His unique blend of academic excellence, research experience, and practical innovation has positioned him to make transformative contributions to healthcare and rehabilitation sciences. With numerous high-impact publications, patents, and international collaborations, he has demonstrated the ability to move ideas from concept to clinical reality. His work directly improves the lives of individuals with neurological disorders while advancing the scientific understanding of brain–machine interaction. As both a leader and mentor, Dr. Lee continues to inspire new research directions in neuroengineering. His commitment to interdisciplinary collaboration, societal impact, and global engagement makes him an exemplary figure deserving of recognition as a top researcher in his field.