Ph.D candidate, Department of Biomedical Engineering, Yonsei University, South Korea
Doljinsuren Enkhbayar is a dedicated biomedical engineer specializing in AI-driven healthcare solutions and biomedical signal processing. Born in Ulaanbaatar, Mongolia, she has a strong background in medical equipment engineering and biomedical data science. With years of experience in both academic research and clinical applications, she is currently pursuing her Ph.D. in Biomedical Engineering at Yonsei University, South Korea. Her passion lies in wearable health technology, biosensors, and the integration of machine learning in medical diagnostics.
Publication Profile
Google Scholar
🎓 Education
Doljinsuren’s academic journey began at the Mongolian University of Science and Technology, where she earned a Bachelor of Engineering in Medical Equipment and Aircraft Maintenance Engineering. She further advanced her expertise with a Master of Science in Biomedical Engineering from the same university. Currently, she is a Ph.D. candidate at Yonsei University, South Korea, focusing on AI and machine learning applications in biomedical sciences.
💼 Experience
With a strong foundation in biomedical engineering, Doljinsuren has worked as a Biomedical Engineer at the National Center of Maternal and Child Health of Mongolia, where she specialized in medical equipment management and safety assessments. She later served as a Training Master in the Department of Electrotechnique at the Mongolian University of Science and Technology, contributing to research and mentoring students. Additionally, she played a pivotal role as a secretariat member of the Mongolian Society of Biomedical Engineering, advocating for technological advancements in healthcare.
🏆 Awards and Honors
Doljinsuren has received multiple accolades for her research excellence. She was awarded the Best Paper Award by the Mongolian Young Scientist Association (2022) for her study on electrosurgical unit output power measurement. She also gained international recognition for her work on predicting esophageal varices using platelet count/spleen size ratio, presented at Chulalongkorn University, Thailand (2020). Her research on chronic hepatitis C treatment was featured at Liver Week 2019 in Busan, Korea.
🔬 Research Focus
Her research interests revolve around AI in healthcare, biomedical signal processing, wearable health technologies, and biosensors. She actively explores how machine learning and biomedical data science can enhance diagnostics, patient monitoring, and medical device performance. Her contributions to biomaterials research, particularly chitosan-based sustainable packaging, reflect her interdisciplinary expertise in biomedical applications.
🔍 Conclusion
Doljinsuren Enkhbayar is a rising expert in biomedical engineering and AI-driven healthcare innovations. Her interdisciplinary research, coupled with her clinical and academic experience, positions her at the forefront of modern medical technology advancements. With an unwavering commitment to improving healthcare outcomes through AI and biomedical data science, she continues to push the boundaries of innovation and research excellence.
📚 Publications
Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes – Published in Bioengineering (2025). Read Here
Chitosan Extracted from the Biomass of Tenebrio molitor Larvae as a Sustainable Packaging Film – Published in Materials (2024). Read Here
Oral Administration of Hydrolysed Casein-Based Supplements on Chronic Liver Disease Patients – Published in The Liver Week (2020). Read Here
Significant Effect of Lifestyle Modification Intervention in Patients with Newly Diagnosed Type 2 Diabetes – Published in The Liver Week (2017). Read Here