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computational imaging

To astronomy and beyond: new AI-driven imaging method turns scattered snapshots into continuous video

U of T's Aviad Levis helped develop an AI-driven method that turns nearly 30 years of telescope observations into a continuous video of a black hole's jet, with uses reaching well beyond astronomy.

$2M from Ontario Research Fund to help scientists demystify black holes

Assistant Professor Aviad Levis and collaborators are developing innovative tools for the imaging black holes with the next generation of radio and optical telescopes. 

U of T computational imaging researchers harness AI to ‘fly’ with light in motion

U of T computational imaging researchers harness AI to ‘fly’ with light in motion

The AI algorithm helps researchers visualize ultrafast videos from any viewpoint, allowing for the study of how light propagates from multiple perspectives.  

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In awarding Nobel Prize, committee cites collaborative black hole research including U of T computer scientist Aviad Levis

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In its scientific background for the 2024 Nobel Prize in Physics, the Nobel Committee notes the relevance of artificial intelligence in astrophysics and astronomy, including the first direct visual evidence of a supermassive black hole at the centre of our galaxy, research involving Assistant Professor Aviad Levis.  

U of T computer scientists develop video camera that acts as a ‘microscope for time’

U of T computer scientists develop video camera that acts as a ‘microscope for time’

Computational imaging researchers have developed a novel technique that allows video from highly dynamic scenes to be recorded once and then slowed down and sped up by a factor of billions.