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Katherine L. (Katie) Bouman
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Phone: 626-395-4140
Home  /  People  /  Katherine L. (Katie) Bouman

Katherine L. (Katie) Bouman

Assistant Professor of Computing and Mathematical Sciences, Electrical Engineering and Astronomy; Rosenberg Scholar; Investigator, Heritage Medical Research Institute
B.S., University of Michigan, Ann Arbor, 2011; M.S., Massachusetts Institute of Technology, 2013; Ph.D., 2017; Visiting Associate, Caltech, 2018-19; Assistant Professor, 2019-; Rosenberg Scholar, 2019-; HMRI Investigator, 2021-.
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Overview

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.

Related News

Researchers Help Generate First Image of Black Hole at the Center of Our Galaxy
New Caltech Center for Sensing to Intelligence (S2I) Launches Collaboration with Industry Partner
Katie Bouman Receives the 2021 Royal Photographic Society Progress Medal
Astronomers Image Magnetic Fields at the Edge of M87's Black Hole
Professor Bouman Featured in Inverse Magazine
Professor Bouman Receives GSC Teaching Award
Katie Bouman Receives Okawa Research Grant
Myra Cheng Receives Goldwater Scholarship
Read more news   >

Publications

View more publications on feeds.library.caltech.edu

Related Courses

2022-23
CS 101 – Special Topics in Computer Science
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