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My research interests are focused on the development and clinical translation of new ultrasound imaging techniques to improve the quality and diagnostic value of ultrasound imaging. My interests are in clinical translation of ultrasound molecular imaging for early cancer detection, improving image quality in difficult-to-image patients, and to reduce noise artifacts in ultrasound images. In my research, I have refined adaptive beamforming methods such as coherence-based imaging, helped to pioneer the use of deep learning tools on raw ultrasound data to produce more accurate B-mode images and more sensitive ultrasound molecular images, and developed GPU-based software beamforming tools to deploy these methods in real-time on experimental and clinical imaging systems.