Assistant Professor of Computing and Mathematical Sciences, Electrical Engineering and Astronomy; Rosenberg Scholar; Investigator, Heritage Medical Research Institute
Katie Bouman's research focuses on computational imaging: designing systems that tightly integrate algorithm and sensor design, making it possible to observe phenomena previously difficult or impossible to measure with traditional approaches. Imaging plays a critical role in advancing science. However, as science continues to push boundaries, traditional sensors are reaching the limits of what they can measure. Katie's group combines ideas from signal processing, computer vision, machine learning, and physics to find and exploit hidden signals for both scientific discovery and technological innovation. For example, in collaboration with the Event Horizon Telescope, Katie's group is helping to build a computational earth-sized telescope that is taking the first images of a black hole and is analyzing its images to learn about general relativity in the strong-field regime.
