John Onofrey, PhD

Dr. John Onofrey conducts basic research to develop and apply novel software solutions to solve clinical problems by combining data science, machine learning and biomedical imaging. A member of the Departments of Radiology and Biomedical Imaging, Urology, and Biomedical Engineering, Dr. Onofrey is the principal investigator of major research funded by the National Institutes of Health. Currently, his interdisciplinary work addresses challenges in prostate cancer diagnosis, liver cancer staging, and positron emission tomography (PET) image analysis.

Dr. Onofrey’s research focuses on the development of novel image analysis algorithms using machine learning, including deep learning methods, and he has a particular interest in image classification, image segmentation, and image registration. He has applied his background in computer science to a wide variety of medical image analysis research projects. His doctoral research focused on leveraging large amounts of clinical data to build effective statistical models of both brain shape and brain deformation for image-guided neurosurgery. As a postdoctoral researcher, Dr. Onofrey applied machine learning towards interventional image-guided biopsy of prostate cancer. He has also applied state-of-the-art machine learning techniques, including deep learning, to automatically segment anatomical structures from clinical images. Not only did these projects leverage large amounts of data to train complex machine learning software algorithms, but they also required detailed software engineering practices to rigorously test and validate these algorithms.

As an educator, Dr. Onofrey co-created and co-teaches the interdisciplinary “Data and Clinical Decision-Making” class in the School of Engineering, which teaches undergraduate and graduate students, and clinical fellows how data science and machine learning are being applied to real-world clinical problems.

Before coming to Yale in 2007, Dr. Onofrey worked as a professional software engineer for the U.S. Army Research Lab (ARL) and Lockheed Martin. He holds a B.S. and M.S. in Computer Science from Johns Hopkins University and a Ph.D. in Biomedical Engineering from Yale University.