Aviad Levis 

I am an Assistant Professor at the University of Toronto, with appointments in the Department of Computer Science, the David A. Dunlap Department of Astronomy & Astrophysics, and the Dunlap Institute for Astronomy & Astrophysics. I develop computational imaging tools for scientific discovery, pushing the limits of what can be observed. My work is interdisciplinary by nature, at the intersection of artificial intelligence and physics.

I lead PI-Vision (Physics-Informed Vision & Imaging), a research group focused on developing new imaging systems and physics-aware algorithms to solve challenging inverse problems across astronomy, Earth observation, and the physical sciences. PI-Vision is part of the broader Toronto Computational Imaging Group, a cross-disciplinary research community spanning computer science, graphics, and the physical sciences at the University of Toronto.

 

My work is supported by the Ontario Research Fund ($2M), NSERC Discovery Grant ($217K), national infrastructure programs (CFI/ORF-RI, $400K), and NSERC RTI ($150K).
 

In the Media.
   “AI reveals a new 3D view of the Milky Way’s black hole” — Space.com
   “Watch a hotspot orbit our galaxy’s black hole” — Sky & Telescope
   “Black hole flares reconstructed in 3D using AI and Einstein’s equations” — Science Friday

Additional coverage in Live Science, ZME Science, and Interesting Engineering.

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Previously, I was a postdoctoral researcher with Katie Bouman at the Computing + Mathematical Sciences (CMS) department at Caltech where I worked on imaging black holes with the Event Horizon Telescope (EHT). ​ Prior to that, I received my Ph.D. from the Technion (EE) under the supervision of Yoav Schechner. Thesis: Volumetric Imaging of the Natural Environment.