Christopher Beaulieu, MD, PhD
Professor of  Radiology, Musculoskeletal Imaging
Three dimensional computer graphics representation of, medical imaging data, including clinical applications of virtual, colonoscopy and arthroscopy; interactive MRI evaluation of joint, motion.
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Robert D. Boutin, MD
Clinical Professor of Radiology, Musculoskeletal Imaging
Adding value to routine radiology exams by translating advancements from fields of artificial intelligence and imaging informatics into clinical use.
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Terry Desser, MD
Professor of Radiology, Abdominal Imaging
Machine learning algorithms for risk stratification of imaging findings in the thyroid gland and the abdomen; natural language processing of free text radiology reports; data mining of medical records for correlation with radiology findings and outcomes.
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Bao H. Do, MD
Clinical Associate Professor of Radiology
Natural language processing of imaging and biomedical text in electronic health records, building real-time decision support systems using qualitative and quantitative features of imaging data, retrospective data mining of imaging text corpus in population studies, leveraging informatics for early cancer detection
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Sergios Gatidis, MD
Associate Professor of Radiology, Pediatric
Medical imaging informatics, machine learning for medical image analysis, pediatric radiology, hybrid imaging, clinical data integration, and clinical translation of AI methods.
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Olivier Gevaert, PhD
Associate Professor of Medicine, Biomedical Informatics & Biomedical Data Science
Biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. Pioneered data fusion work using Bayesian and kernel methods studying breast and ovarian cancer. Additionally, developed computational algorithms for the identification of driver genes using multi-omics data. 
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Aya Kamaya, MD
Professor of Radiology, Body Imaging
Hepatobiliary imaging and HCC screening, surveillance, and diagnosis; quantitative evaluation of enhancement to help predict risk of malignancy using contrast-enhanced US and perfusion CT; thyroid cancer imaging and risk stratification.
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Nishita Kothary, MBBS
Professor of Radiology, Interventional Radiology
Interventional Oncology: Percutaneous and transarterial interventions for diagnosis and treatment of primary and metastatic tumors (lung, liver and renal); Research Interest: Gastrointestinal and Hepatic Oncology
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David Larson, MD, MBA
Professor of Radiology, Pediatric
Quality measurement and improvement in radiology, CT radiation dose optimization, probability modeling of likelihood of acute appendicitis in children based on ultrasound
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Ann Leung, MD
Professor of Radiology, Thoracic Imaging 
Computed tomography of the thorax, particularly its application in the setting of acute lung disease in the immunocompromised host; quantitative assessment of abnormalities, using spiral CT; and enhancement characteristics of lung cancers on CT and MRI
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Ruijiang Li, PhD
Associate Professor of Radiation Oncology, Radiation Physics
Development of quantitative imaging biomarkers for prognostication and prediction of therapy response in cancer. Integrate multi-modality imaging and employ advanced image analysis and statistical/machine learning tools to aid the discovery of novel imaging characteristics with clinical relevance. 
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Ying Lu, PhD
Professor of Biomedical Data Science 
Biostatistics, clinical trials, statistical evaluation of medical diagnostic tests, radiology, osteoporosis, meta-analysis, and medical decisoin making.
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Parag Mallick, PhD
Associate Professor of Radiology, Cancer Early Detection
Apply systems biology's complimentary computational and experimental methods in hopes that experimental results motivate large-scale computational studies, which initiate new experimental explorations. We hope this synergistic combination will provide insight into the relationship between molecular phenomena and organismic phenomena.
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Bruno Passebon Soares, MD
Associate Professor of Radiology, Pediatric
Implementation of new clinical MRI protocols in pediatric neuroimaging with the goal of making data accessible to several research initiatives.
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Killian M. Pohl, PhD
Associate Professor of Psychiatry and Behavioral Sciences
Computational neuroscience aimed at identifying biomedical phenotypes to improve the mechanistic understanding, diagnosis, and treatment of neuropsychiatric disorders.
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Emily Tsai, MD
Clinical Associate Professor of Radiology
Lung cancer screening, interstitial lung disease characterization, biomarkers, CT-guided procedures and radiology-pathology correlation, opportunistic screening, clinical applications of AI/machine learning
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