Physics and AI with Katie Bouman

Illuminating the Hidden Universe with Physics and AI with Katie Bouman

Learn how scientists are combining novel and classical tools to create images of things that are difficult—or even fundamentally impossible—to observe directly.

Advance registration for this event is full. Guests who have not pre-registered are invited to join our standby line. We recommend you arrive no later than 6:50 p.m. for standby.

Date: Wednesday, November 4, 2026
Time: 7:30 p.m. PT
Where: Beckman Auditorium
Admission: Free, but registration is required

Join the Caltech Public Events mailing list to receive email notifications about the Watson Lectures and other public events.

About Bouman's Talk

Some of the most iconic images in modern science were never captured by a camera in the traditional sense. Instead, they were inferred from indirect and incomplete measurements, using a careful combination of physics, prior knowledge, and computation.

In this talk, Katie Bouman will explore how physics and artificial intelligence (AI) are working together to illuminate parts of the universe that are difficult—or even fundamentally impossible—to observe directly. It begins with the story of black hole imaging, where theory long predicted what we should see, and where confidence came not from a single image, but from the consistency of features across many reconstructions of the same data. This kind of inference is not unique to extreme astrophysics, but it also underlies how researchers form images in familiar technologies they rely on every day.

In this talk, Bouman will demonstrate how simple assumptions can take us far, but she will also explain where these assumptions begin to limit what we can learn, and how modern AI methods provide new ways to explore richer possibilities while still respecting physical laws. More broadly, this talk explores a shift in scientific imaging: As we push the boundaries of observation, images are increasingly constructed rather than simply captured, and understanding how they are made is essential to interpreting what they show.

About the Speaker

Katie Bouman is a professor of computing and mathematical sciences, electrical engineering and astronomy; Rosenberg Scholar; and Heritage Medical Research Institute Investigator.

Credit: Lance Hayashida/Caltech

Her 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. Bouman'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.

Prior to starting at Caltech, Bouman was a postdoctoral fellow with the Event Horizon Telescope, which published the first picture of a black hole in April 2019.

She has received accolades including the Presidential Early Career Award for Scientists and Engineers (PECASE), a Sloan Fellowship, an NSF CAREER Award, the Electronic Imaging Scientist of the Year Award, the Royal Photographic Society Progress Medal, and a Caltech faculty teaching award, and was a co-recipient of the Breakthrough Prize.