After earning a Ph.D. in physics from Cornell University, Courosh Mehanian changed course to pursue a career doing research in the areas of machine learning and computer vision. He has made contributions in neural networks for early visual processing, automatic target recognition, semiconductor quality control, automated pap-smear interpretation, computer-aided diagnosis in digital pathology for drug safety testing, and data mining in large datasets using big data technologies. He has held positions at Boston University, MIT Lincoln Laboratory, Cytyc, KLA-Tencor, Charles River Laboratories, Globys, and Staples Innovation Labs.He most recently served as a principal investigator of the machine learning group at Global Health Laboratories in Bellevue, Washington. The team is charged with applying machine learning towards the solution of a variety of global health problems. The team has developed algorithms for the automated detection and counting of malaria parasites in microscope images of blood smears; the automated detection of precancerous lesions in mobile-phone images; and the automated detection of childhood pneumonia using hand-held ultrasound transducers.