AI, Radio Astronomy, and the Search for Life Beyond Earth
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Episode description
Radio astronomy combines astronomy, physics, signal processing, engineering, and computing to study the Universe through radio-frequency observations. As modern radio telescopes generate vast volumes of data, AI is becoming an essential tool for advancing the search for extraterrestrial intelligence (SETI). In this talk Ramiro Caisse Saide will present a multimodal deep-learning approach for technosignature detection using observations from the Breakthrough Listen backend at MeerKAT. He will share investigations into whether combining spectrograms with in-phase and quadrature (I/Q) signal representations can improve signal detection and classification, particularly in low signal-to-noise environments where traditional spectral features become less distinct. Speaker(s): Ramiro Caisse Saide, University of Manchester Host(s): Samuel Maina, Felermino Ali, Microsoft See more at https://www.microsoft.com/en-us/research/video/ai-radio-astronomy-and-the-search-for-life-beyond-earth/
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