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Katie Bouman's research focuses on computational imaging, specifically designing systems that tightly integrate algorithms with sensor design. This work enables the observation of phenomena that have previously been difficult or impossible to measure with traditional approaches. Imaging plays a critical role in advancing scientific understanding; however, traditional sensors are nearing their limits. Bouman’s group combines concepts from signal processing, computer vision, machine learning, and physics to uncover hidden signals, driving both scientific discovery and technological innovation. Notably, through collaboration with the Event Horizon Telescope, Bouman's team is contributing to the development of a computational, earth-sized telescope to capture images of black holes and analyze these images to enhance our understanding of general relativity within the strong-field regime.
California Institute of Technology • Pasadena, CA
Professor in the Department of Computing and Mathematical Sciences, Department of Electrical Engineering, and Department of Astronomy. Rosenberg Scholar and Investigator at the Heritage Medical Research Institute.
California Institute of Technology • Pasadena, CA
California Institute of Technology • Pasadena, CA
California Institute of Technology • Pasadena, CA
Most Caltech graduate programs are PhD-only. GRE General and Subject tests vary by department; many have made them optional or no longer accept them.