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Dr. Lay received his PhD in Computational Science from Florida State University in 2013 where he developed a novel machine learning aggregation framework based on ideas from prediction markets. He spent three years in industry research where he developed methods for segmentation and landmark localization in medical image analysis problems. As a result of his work in the industry, he is a co-inventor of several patents. After three years of industry research, he joined the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory at the National Institutes of Health as a Staff Scientist where he developed novel prostate cancer detection methods. Through close collaboration with the Molecular Imaging Program, his prostate cancer detection systems have been honed and studied in three international reader studies. His research interests are in the fields of machine learning and computer vision.