Watson Lecture Promo – November 4, 2026: Katie Bouman
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Watson Lecture Promo – November 4, 2026: Katie Bouman
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Illuminating the Hidden Universe with Physics and AI with Katie Bouman
Wednesday, November 4, 2026
6 p.m. — Activities and music. Food, drinks, and books available for purchase
7 p.m. — Doors open
7:30 p.m. — Talk and Q&A
8:30 p.m. — Post-talk concessions and conversation.
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.
More info and RSVP: https://www.caltech.edu/campus-life-events/calendar/watson-lecture-katie-bouman
Wednesday, November 4, 2026
6 p.m. — Activities and music. Food, drinks, and books available for purchase
7 p.m. — Doors open
7:30 p.m. — Talk and Q&A
8:30 p.m. — Post-talk concessions and conversation.
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.
More info and RSVP: https://www.caltech.edu/campus-life-events/calendar/watson-lecture-katie-bouman
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