David Lindell

David Lindell is an Assistant Professor in the Department of Computer Science at the University of Toronto. His research interests include computer graphics, computer vision, machine learning, computational imaging, 3D computer vision, time-of-flight imaging, and physics-based machine learning. He is a faculty affiliate at the Vector Institute, a faculty fellow at AXL, and a founding member of the Toronto Computational Imaging Group. His work focuses on physically based intelligent sensing, combining physically based models, signal processing, and artificial intelligence to enhance sensing systems and reconstruct the world from visual information.

David Lindell is an Assistant Professor at the University of Toronto, specializing in Computational Imaging, Computer Vision, and Machine Learning. His research focuses on advancing imaging technologies through innovative computational methods, including non-line-of-sight imaging, neural scene representation, and 3D imaging through scattering media. Lindell's work integrates deep learning with physical models to enhance imaging capabilities, particularly in challenging environments such as scattering media and low-light conditions. His publications explore topics like implicit neural representations, fast f-k migration, and sensor fusion techniques, contributing to the development of advanced imaging systems and generative models for 4D content creation.