Affiliated Faculty

Chris Beaulieu, MD, PhD
Professor of  Radiology, Associate Chair of Education
Three dimensional computer graphics representation of, medical imaging data, including clinical applications of virtual, colonoscopy and arthroscopy; interactive MRI evaluation of joint, motion.

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.

Bao H. Do, MD
Clinical Assistant Professor (Affiliated) 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

Ahmed El Kaffas, PhD
Instructor of  Radiology
Quantitative ultrasound methods to characterize tissues. The aim is to relate quantitative imaging parameters from different ultrasound-based imaging modes to biomarkers that can be used for disease surveillance, diagnosis and treatment monitoring/characterization. 

Olivier Gevaert, PhD
Assistant Professor of Medicine - Biomedical Informatics Research
Biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. Previously we 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. 
Email | Website

Robert J. Herfkens, MD
Professor of Radiology, Emeritus
Imaging of cardiovascular diseases with CT, magnetic resonance imaging and spectroscopy

Aya Kamaya, MD
Professor of Radiology, Interim Division Chief of Body Imaging
Research interests include 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.

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

David Larson, MD, MBA
Professor of Radiology, Pediatric Radiology
Vice Chair of Education and Clinical Operations
Quality measurement and improvement in radiology, CT radiation dose optimization, probability modeling of likelihood of acute appendicitis in children based on ultrasound

Ann Leung, MD
Professor of Radiology, (Thoracic Imaging), Division Chief of Thoracic Imaging, Associate Chair of Clinical Affairs
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

Ruijiang Li, PhD
Assistant Professor (Research) 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. 
Email | Website

Ying Lu, PhD
Professor of Biomedical Data Science and, by courtesy, Radiology (Molecular Imaging Program)
Research interests include biostatistics, clinical trials, statistical evaluation of medical diagnostic tests, radiology, osteoporosis, meta-analysis, and medical decisoin making.

Matthew Lungren, MD, MPH
Associate Professor of Radiology (Pediatric Radiology)
Research interests include natural language processing and statistical data modeling for predicting imaging test outcomes, data mining as an approach for epidemiologic problem solving, building integrative clinical support tools, and deep learning for medical image analysis.  

Parag Mallick, PhD
Associate Professor of Radiology (Canary Center)
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.
Email | Website

Andrew Ng, PhD
Adjunct Professor of Computer Science and Electrical Engineering
Research interests include AI, Machine Learning, Deep Learning, and the applications of these techniques to healthcare. Particular interest in conversational agents (e.g., Melody the Medical Assistant), medical imaging, and machine learning from EHR. 
Email Website

David Paik, PhD
Director of Imaging Science at Elucid Bioimaging Inc.
Dr. Paik's research interests lie at the intersection of radiology, molecular biology and informatics. He focuses on developing and validating computational methodologies for extracting useful information content from anatomic, functional and molecular images, drawing upon image processing, computer vision, computer graphics, computational geometry, machine learning, biostatistics, modeling and simulation.

Killian M. Pohl, PhD
Associate Professor of Psychiatry and Behavioral Sciences
Medical Image Analysis