Close Modal Beyond the Telescope: Unveiling the Invisible Milky Way with AI Take an AI-powered tour of the Milky Way in this immersive Planetarium program featuring MIT astrophysicist Lina Necib, PhD. Using real Gaia Space Observatory data and advanced machine learning technology, uncover the hidden forces shaping our galaxy—from epic cosmic collisions to the elusive nature of dark matter. Image What if we could see what lies beyond the limits of our telescopes?Join MIT professor and astroparticle physicist Dr. Lina Necib on a journey through our Milky Way featuring real data from the revolutionary Gaia Space Observatory, artificial intelligence techniques, and the cutting-edge technology and immersive data visualization systems of the Planetarium. Explore all that lies within our home galaxy — from the observable and expected, to the mysterious and invisible, and discover how astronomers apply novel machine learning techniques to the most massive cosmic smash-ups, galactic collisions, and mergers to understand one of the most enigmatic substances in the universe: dark matter! Whether you're a space enthusiast, science lover, or simply curious about the unknown, this groundbreaking program blends science, technology, and creativity to illuminate our place in the cosmos.See what AI can reveal — beyond the telescope. Register for the Event Date and Time Wednesday, August 13 | 7:00 pm Audience 9-12th grades (High school), Adults 18+ Location Charles Hayden Planetarium View Map Price Free with Pre-Registration Language English Register for the Event Date and Time Wednesday, August 13 | 7:00 pm Audience 9-12th grades (High school), Adults 18+ Location Charles Hayden Planetarium View Map Price Free with Pre-Registration Language English What if we could see what lies beyond the limits of our telescopes?Join MIT professor and astroparticle physicist Dr. Lina Necib on a journey through our Milky Way featuring real data from the revolutionary Gaia Space Observatory, artificial intelligence techniques, and the cutting-edge technology and immersive data visualization systems of the Planetarium. Explore all that lies within our home galaxy — from the observable and expected, to the mysterious and invisible, and discover how astronomers apply novel machine learning techniques to the most massive cosmic smash-ups, galactic collisions, and mergers to understand one of the most enigmatic substances in the universe: dark matter! Whether you're a space enthusiast, science lover, or simply curious about the unknown, this groundbreaking program blends science, technology, and creativity to illuminate our place in the cosmos.See what AI can reveal — beyond the telescope. Featuring Lina Necib, PhD Assistant Professor of Physics, MIT Dr. Lina Necib is an astroparticle physicist whose work focuses on understanding dark matter. Originally from Tunisia, she moved to the United States in 2008 and earned a bachelor’s degree in physics from Boston University in 2012. She received her PhD in particle physics from MIT in 2017, working under the supervision of Professor Jesse Thaler.She was a Sherman Fairchild Fellow at Caltech from 2017 to 2020, then held fellowships at both UC Irvine and the Carnegie Observatories. In 2021, she joined the faculty at MIT as an assistant professor of physics in theoretical astrophysics.Dr. Necib is currently a senior investigator at the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) and one of the principal investigators of the FIRE (Feedback In Realistic Environments) collaboration. Image IAIFI Institute for Artificial Intelligence and Fundamental Interactions The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) is a collaboration of physics and AI researchers at MIT, Harvard, Northeastern, and Tufts, working to pioneer interdisciplinary AI+Physics research; empower the next generation of AI+Physics talent; and build a dynamic AI+Physics community. Developed in Partnership with Image OpenSpace is funded in part by NASA under award No NNX16AB93A. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration.
