황재윤
Hwang, Jae YounDepartment of Electrical Engineering and Computer Science
학력
- 2004 ~ 2009Univ of Southern California 박사
- 2001 ~ 2003서울대학교 석사
- 1999 ~ 2001고려대학교 학사
경력
- 2012 ~ 2014Univ. of Southern California / Research Associate
- 2009 ~ 2012Cedars-Sinai Medical Center / 박사후연구원
수상실적
- 2016 공로상 / DGIST
- 2009 Grodin symposium Best poster award / Univ. of Southern California
- 2008 Frederick Urbach Travel Award / American Society for Photobiology
- 2004 한국과학재단 대학원 펠로우십 / 한국연구재단
연구실 소개
- Multimodal Biomedical Imaging and System Laboratory
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Our goal is to develop a novel multimodal imaging system and mobile healthcare device for early detection of various diseases with optical and high-frequency ultrasound techniques. In particular, our current research interests include development of a mobile healthcare imaging system for skin care, a multimodal endoscope for localization and delineation of malignant gastric lesions, and high-frequency ultrasound microbeam techniques for probing cell mechanics.
Related Keyword
- "Expert-level differentiation of incomplete Kawasaki disease and pneumonia from echocardiography via multiple large receptive attention mechanisms", Lee, Haeyun. (2025-09). Expert-level differentiation of incomplete Kawasaki disease and pneumonia from echocardiography via multiple large receptive attention mechanisms. Computers in Biology and Medicine, 195. doi: 10.1016/j.compbiomed.2025.110478
- "SoN: Selective Optimal Network for smartphone-based indoor localization in real-time", Lee, Kyungsu. (2025-05). SoN: Selective Optimal Network for smartphone-based indoor localization in real-time. Expert Systems with Applications, 272. doi: 10.1016/j.eswa.2025.126639
- "Machine Learning-Enhanced Skull-Universal Acoustic Hologram for Efficient Transcranial Ultrasound Neuromodulation Across Varied Rodent Skulls", Lee, Moon Hwan. (2025-01). Machine Learning-Enhanced Skull-Universal Acoustic Hologram for Efficient Transcranial Ultrasound Neuromodulation Across Varied Rodent Skulls. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 72(1), 127–140. doi: 10.1109/TUFFC.2024.3506913
- "Intelligent Bladder Volume Monitoring for Wearable Ultrasound Devices: Enhancing Accuracy through Deep Learning-based Coarse-to-Fine Shape Estimation", Lee, Kyungsu. (2024-07). Intelligent Bladder Volume Monitoring for Wearable Ultrasound Devices: Enhancing Accuracy through Deep Learning-based Coarse-to-Fine Shape Estimation. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 71(7), 775–785. doi: 10.1109/TUFFC.2024.3350033
- "Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models", Kim, Jeong-Whun. (2024-07). Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models. American Journal of Respiratory and Critical Care Medicine, 210(2), 211–221. doi: 10.1164/rccm.202304-0767OC
- "Connectome Mapping: Shape-Memory Network via Interpretation of Contextual Semantic Information", Lee, Kyungsu. (2025-04-25). Connectome Mapping: Shape-Memory Network via Interpretation of Contextual Semantic Information. International Conference on Learning Representations, 69747–69775.
- "Evaluation of Few-Shot Detection of Head and Neck Anatomy in CT", Lee, Kyungeun. (2024-02-19). Evaluation of Few-Shot Detection of Head and Neck Anatomy in CT. Medical Imaging 2024: Computer-Aided Diagnosis, 1–7. doi: 10.1117/12.3006895
- "Explainable Multiple Receptive Attention Network for Expert Cardiologist Compatible Incomplete Kawasaki Disease Diagnosis on Echocardiography", Lee, Kyungsu. (2024-02-05). Explainable Multiple Receptive Attention Network for Expert Cardiologist Compatible Incomplete Kawasaki Disease Diagnosis on Echocardiography. 1st IEEE International Conference on Artificial Intelligence for Medicine, Health and Care, AIMHC 2024, 243–250. doi: 10.1109/AIMHC59811.2024.00050
- "Compensating for Size Effect in Shear Wave Elastography Using Deep Neural Networks", Lee, Seungyeop. (2023-10-19). Compensating for Size Effect in Shear Wave Elastography Using Deep Neural Networks. International Conference on Control, Automation and Systems, ICCAS 2023, 1304–1307. doi: 10.23919/ICCAS59377.2023.10316907
- "Fine-Tuning Network in Federated Learning for Personalized Skin Diagnosis", Lee, Kyungsu. (2023-10-10). Fine-Tuning Network in Federated Learning for Personalized Skin Diagnosis. International Conference on Medical Image Computing and Computer Assisted Intervention, 378–388. doi: 10.1007/978-3-031-43898-1_37
연구 뉴스
- DGIST Develops World’s Best Performance Technology for Aerial and Satellite Image Extraction through Industry-Academic Cooperation with Dabeeo Inc. 2024-04-15
- DGIST, 주식회사 다비오와 산학협력 통해 세계 최고 성능 항공·위성 영상 추출 기술 개발! 2024-04-11
- DGIST Professor Hwang Jae-yoon's Team Writes Letters with Ultrasonic Beam! Develops Deep Learning based Real-time Ultrasonic Hologram Generation Technology 2023-01-03
- DGIST 황재윤 교수팀. 초음파 빔으로 문자를 그리다! 딥러닝 기반 실시간 초음파 홀로그램 생성 기술 개발 2022-12-08
- 기존 의료 광학 영상의 한계, 세계 최초‘초음파 조직 투명화’기술로 극복! 2022-09-19
연구분야
미래유망 신기술(6T)
국가과학기술표준분류