Dr. Kim’s research interests are mainly in developing cutting-edge image analysis methods for the interdisciplinary field between computer science and biomedicine. Imaging data has become the most powerful tool in biomedicine due to the advancement of high-resolution imaging technology and the increasing variety of imaging modalities. She aims to apply state-of-the-art computer science technologies, for example, machine/deep learning, pattern recognition, computer vision, visualization, and graph theory, to various clinical and preclinical research imaging data to study biomedical fundamentals from computer scientists’ view. Such techniques can be adapted to healthcare practices and biomedical research for automated image reading/quantification, computer-assisted diagnosis at an earlier time as well as predictive modeling for clinical outcome.
