My research is broadly in the interdisciplinary studies that integrates computer vision, diagnostic imaging, quantitative image analysis, bioinformatics, artificial intelligence (AI) and machine learning to increase the sensitivity of radiological lesion detection, and to characterize abnormalities and their likelihood of being significant, for diagnosis, treatment assessment and clinical decision making. I have been collaborating with multidisciplinary physicians and researchers including radiologists, pathologists, pulmonologists, hematologists, oncologists, medical physicists and computer scientists, and training/teaching postdocs and student research assistants. I have been a principal investigator (PI) and a co‐investigator on many NIH and DOD grants, directing and conducting researches in optimization of image quality, development of computer‐aided detection and diagnosis (CAD), and diagnostic decision support systems (DSS) for a variety of diseases, including pulmonary embolism and other pulmonary diseases, coronary artery disease (CAD), multiple myeloma (MM), lung cancer, bladder cancer, breast cancer, with CT, MRI, mammography, ultrasound, and digital pathological images. I have published over 180 articles in peer‐reviewed journals and international conference proceedings and made over 200 presentations/exhibits at international conferences. I was named as a Distinguished Investigator of the Academy of Radiology Research in 2013. I am a member of the Quantitative Imaging Biomarker Alliance (QIBA), Consortium for Imaging and Biomarkers (CIB) and Quantitative Imaging Network (QIN) and have been serving professional communities as a grant reviewer for NIH, Army-CDMRP and international grant of KWF cancer research in Netherland, associate editor of Medical Physics and reviewer for a variety of peer-reviewed journal and giving invited talks both nationally and internationally.