معرفی
Michael Langer is an Associate Professor at the School of Computer Science, McGill University, and a member of the Center for Intelligent Machines (CIM). His research focuses on computational models of vision, particularly how vision systems estimate 3D scene properties such as shape, layout, materials, and lighting using cues like shading, shadows, specular reflection, defocus blur, motion parallax, and binocular disparity.
- B.Sc. in Mathematics from McGill University
- M.Sc. in Computer Science from the University of Toronto
- Ph.D. in Computer Science from McGill University
Langer's work explores both human and computer vision, with a strong emphasis on depth perception, 3D clutter analysis, and the use of visual cues to infer scene geometry. His recent publications highlight advancements in depth estimation from defocus, 3D scene statistics, and stereo vision.
Scientific awards include the Itek Award (best student paper in 2022 IS&T journals) and the Best Vision Paper Award (Canadian Conference on Computer and Robot Vision, 2007). He has supervised numerous M.Sc., Ph.D., and undergraduate research students, with a focus on computational modeling in vision and graphics courses.
His lab at CIM integrates interdisciplinary research in computer vision, psychophysics, and image processing, often collaborating with institutions like the NEC Research Institute and the Max Planck Institute for Biological Cybernetics.
