Jae Ho Sohn

Jae Ho Sohn, MD, MS, is an Assistant Professor in the Department of Radiology at the University of California, San Francisco (UCSF), School of Medicine. His research focuses on cardiothoracic radiology, particularly lung cancer and interstitial lung disease imaging, with a technical emphasis on machine learning, quantitative imaging, and clinical translation of 0.55T low-field lung MRI. He also serves as an education co-chair of the UCSF Center for Intelligent Imaging, mentoring students in data science projects in radiology.

Education: Johns Hopkins University (BA and MS in Applied Math & Statistics), Geisel School of Medicine at Dartmouth (MD), and UCSF (Clinical Fellowship in Cardiothoracic Imaging, T32 Research Fellowship in Big Data in Radiology, Residency in Diagnostic Radiology).

Research interests include lung cancer screening, interstitial lung abnormalities, big data imaging biomarkers, radiological text processing, and integration of AI into clinical practice. Notable projects involve longitudinal lung nodule tracking, automated radiology protocoling, and prediction of healthcare costs from chest radiographs.

His team's work has received media coverage from outlets like the Washington Post and Scientific American. Awards include the RSNA Resident/Fellow Research Grant (2020) and the global oncology award from the Stanford Health++ hackathon. Students under his mentorship have won RSNA trainee research prizes and scholarships.

He is actively recruiting students, scientists, and post-doctoral scholars for projects in radiology data science and AI integration.