Faculty & Staff

Kyle Lafata is an Assistant Professor of Radiology, Radiation Oncology, and Electrical & Computer Engineering at Duke University. As an imaging physicist and data scientist, Dr. Lafata’s research interests are in image-based phenotyping and computational biomarkers. His dissertation work focused on nature-inspired computational methods and soft-computing paradigms, including the applied analysis of stochastic differential equations, self-organization, and quantum machine learning (i.e., an emerging branch of research that explores the methodological and structural similarities between quantum systems and learning systems). He has broad expertise in imaging science, digital pathology, computer vision, feature engineering, and applied mathematics.

The Lafata Laboratory focuses on multi-scale imaging biomarkers. They study the imaging phenotype across multiple physical length-scales, including radiological (i.e., ~10^-3 m), pathological (i.e., ~10^-6 m), and molecular (i.e., ~10^-9 m) domains. The lab develops mathematical methods, physics-based models, computational imaging techniques, and data fusion algorithms to quantify the appearance and behavior of disease across space and time. This technology is applied to interrogate underlying biology, characterize tissue microenvironments, diagnose disease, quantify treatment response, and enable personalized therapy.