Mr. Jiseong Byeon at Department of Industrial and Systems Engineering, Dongguk University, South Korea.
Jiseong Byeon is a passionate and emerging researcher in the field of artificial intelligence and computer vision, currently pursuing an M.S. in Industrial and Systems Engineering at Dongguk University, Seoul. With a multidisciplinary academic background combining global business and systems engineering, Jiseong brings a unique blend of strategic thinking and technical expertise. His research is centered around the development of intelligent image-based systems, particularly in the medical domain. He has experience working with advanced deep learning frameworks and has contributed to projects involving 3D human modeling and predictive analytics. Known for his curiosity and collaborative spirit, he aims to advance healthcare and human-computer interaction through innovative AI models. 📸🧠💡
Professional Profile
ORCID
🎓 Education
Jiseong Byeon is currently enrolled in a Master’s program in Industrial and Systems Engineering at Dongguk University, Seoul, beginning in September 2024. He previously earned his Bachelor of Arts in Global Business from Dong-A University in Busan, graduating in August 2024. His educational journey has been a unique blend of global business principles and technical problem-solving, giving him a diverse perspective on interdisciplinary research. During his undergraduate years, Jiseong began exploring data science and AI applications, which led him to transition fully into research-focused engineering. Through academic coursework, hands-on lab experiences, and independent study, he has built a solid foundation in data analytics, deep learning, and applied computer vision techniques. 🏫📚🧑🎓
💼 Experience
Jiseong Byeon has amassed valuable research experience across both undergraduate and graduate levels. Currently serving as a Graduate Researcher at Dongguk University since September 2024, he is engaged in developing models for 3D human body reconstruction using Vision Transformer architectures. This cutting-edge work aims to transform how AI interprets and renders human anatomy in digital formats. Previously, from March 2022 to August 2024, he worked as an Undergraduate Research Assistant at Dong-A University. There, he contributed to building encoding-based click prediction models and performed in-depth crime factor analysis using Seoul city data. These diverse experiences have honed his data interpretation skills and technical creativity, preparing him for advanced research and real-world AI application. 🖥️🔍📊
🔬 Research Interests
Jiseong Byeon’s research interests lie at the intersection of artificial intelligence, computer vision, and human modeling. His key areas include Image-to-Image Translation using the Pix2Pix framework, 3D Human Body Modeling, and Vision Transformers for medical applications. He is deeply motivated to apply deep learning algorithms to tasks that require detailed visual interpretation—especially those in the medical field where accurate prediction can significantly enhance outcomes. His work also explores how AI can be used for real-time inference and post-surgical visualization, such as predicting body shape changes. Additionally, Jiseong is keen on exploring the scalability of such models for widespread, ethical, and efficient implementation. 🤖🧬👨⚕️
🏆 Awards
While still early in his research career, Jiseong Byeon has shown exceptional promise and has been consistently recognized by his academic mentors for his innovation and diligence. He has been nominated for several internal research awards at Dong-A University, particularly for his work on crime prediction modeling and click prediction systems. His transition to graduate-level research was also supported by faculty recommendations based on the excellence of his undergraduate research projects. With his first peer-reviewed publication accepted and increasing involvement in high-impact research domains, he is a strong candidate for early-career research recognition and award nominations. 🏅📈🌟
📚 Top Noted Publications
Byeon has contributed to a peer-reviewed article that showcases the application of deep learning in medical image analysis:
The paper titled “Predicting Post-Liposuction Body Shape Using RGB Image-to-Image Translation” by Kim, M., Byeon, J., Chang, J., and Youm, S., published in Applied Sciences in 2025, presents a novel approach to forecasting post-liposuction body contours using RGB image-to-image translation techniques.
Key Details:
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Authors: M. Kim, J. Byeon, J. Chang, and S. Youm
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Publication Year: 2025
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Journal: Applied Sciences
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Citation Count: Cited by 3 articles as of 2025
Research Highlights:
The study focuses on leveraging RGB image-to-image translation methods to predict the outcomes of liposuction procedures. By utilizing preoperative images, the model aims to generate realistic visualizations of post-surgical body shapes, enhancing patient consultations and surgical planning.
Related Works:
While direct citations of this paper are limited, related research in the domain includes:
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Development of a Non-Contact Sensor System for Converting 2D Images into 3D Body Data: This study introduces a deep learning approach to generate 3D body models from 2D images, facilitating obesity monitoring and body shape analysis. scholarworks.dongguk.edu+2Dongguk University+2MDPI+2
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Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values: This research emphasizes the use of 3D body data to enhance obesity diagnosis models, reflecting detailed body type information. MDPI+4ResearchGate+4MDPI+4
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Predictive Model for Abdominal Liposuction Volume in Patients with Obesity Using Machine Learning: This study develops a machine learning model to predict liposuction volumes, aiding in surgical planning for obese patients.
Conclusion
Jiseong Byeon is a highly promising early-career researcher with a strong foundation in computer vision, deep learning, and real-world applications. His current trajectory suggests significant potential for future impact in both academic and applied AI research. While it may be slightly early for a top-tier “Best Researcher Award”, he is exceptionally well-positioned for a “Rising Star” or “Promising Researcher” recognition. With continued publication, international exposure, and leadership development, he could become a strong contender for major awards in the near future.