Black Holes, Dark Matter, and AI: Imaging the Hidden Universe - Katie Bouman - 05/29/2026

How do scientists use AI, physics, and telescope observations to "photograph" black holes, dark matter, and other exotic astrophysical phenomena? Join us for a lecture by Professor Katie Bouman, member of the Event Horizon Telescope (EHT) that took the first picture of a black hole, as she discusses these novel analytic techniques. Her presentation will be followed by a panel Q&A consisting of several astrophysicists to answer your questions about astronomy and space science. Timestamps and description below: 00:00 Start of Stream 00:11 Announcements 5:13 Introduction of Presenter 6:55 Start of Presentation but Microphone Off 8:04 Black Hole Presentation 42:16 End of Presentation 42:25 Black Hole Q&A 42:35 "What is the inferred velocity the material around Sgr A*?" 44:28 "Should there be 'hard edges' in the image of the black hole?" 46:39 "Can the movement of the Earth increase the EHT aperture size to get better images?" 47:52 "How can EHT photograph black holes with all the stars and gas in the way?" 52:10 Intermission 58:01 Q&A Panel Introductions 1:01:39 "What will be the fate of our Universe: big rip, big freeze, or big crunch?" 1:06:23 "What were the biggest challenges in producing the EHT black hole images?" 1:09:38 "How have diffusion models affected how you treat data noise?" 1:13:58 "Is there a way to validate outputs from AI to ensure they're useful?" 1:17:09 "Can the EHT photograph the jets from these black holes?" 1:21:17 "What is the source of the light that we see in the EHT images of black holes?" 1:24:17 "What can you tell us about where dark matter exists in the Universe?" 1:29:05 "How unique are different black holes? Or are they really similar in nature?" 1:34:40 "Are the lobes we see around the black holes in EHT images real?" 1:35:33 "Are there planets orbiting around binary and triple star systems? Are they stable?" 1:38:36 "What is the end stage of galaxies? Can galaxies die?" 1:40:30 "What forms of bias do you find in your AI methods to image black holes?" 1:46:24 "Why are dark matter structures spherical and not disky?" 1:52:18 "Are Sgr A* and M87 the only two black holes we can observe?" 1:54:29 "The intergalactic medium has been neutral and ionized--will it be ionized forever?" 1:59:22 Concluding Remarks Title: Images of the Hidden Universe Lecturer: Katie Bouman Abstract: 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 combination of physics, prior knowledge, and computation. In this talk, I will explore how physics and machine learning are working together to illuminate parts of the universe that are difficult -- or even fundamentally impossible -- to observe directly. I’ll begin with the story of how our Event Horizon Telescope team created the first direct image of a black hole. Theory had long predicted what we should see, and confidence came not from a single image, but from the consistency of features across many reconstructions of the same data. I will discuss how these ideas extend beyond black holes to other scientific imaging problems, including mapping the distribution of dark matter from subtle distortions in the shapes of galaxies due to gravitational lensing. Together, these examples illustrate how modern imaging increasingly relies on integrating physics and machine learning to extract meaningful information from fundamentally limited data to uncover our hidden universe.