Key Research Interests

Deep learning based medical image analysis

• Automatic measurement of clinical parameters using deep learning based segmentation and detection

• Controllable computation algorithms for clinically reliable medical image analysis

Deep learning driven ultrasound imaging

• Unsupervised and self-supervised learning for high-quality ultrasound image reconstruction

• Deep learning based inverse problem solving for artifact reduction

• Deep learning based quantitative imaging and perfusion imaging

Data-efficient and computation-efficient deep learning

• Physics-informed pseudo data generation for data-efficient deep learning

• Unsupervised and self-supervised learning for medical image analysis

• Model compression and acceleration using hardware accelerators

• Hardware-aware neural architecture searching for medical applications

Education

• Ph.D., Department of Electronic Engineering, Sogang University, Seoul, Korea (2020-)

• B.E., Department of Electronic Engineering, Sogang University, Seoul, Korea (2015-2020)

Awards

• Best Paper Award, Department of Electronic Engineering, Sogang University, 2023.

• The Young Investigator Prize, The 19th World Federation for Ultrasound in Medicine and Biology Congress (WFUMB), 2023.

• Best Poster Award, International Symposium on Integrated Medical Solutions (iSims), 2023.

• Young Investigator Award - Gold, The 54th Annual Congress of Korean Society of Ultrasound in Medicine (KSUM), 2023.

Community Involvement

• Reviewer, Computers in Biology and Medicine (Elsevier)

• Reviewer, Expert Systems with Applications (Elsevier)

• Reviewer, Access (IEEE)

• Reviewer, Biomedical Engineering Letters (Springer)

• Student Member, IEEE