Davi Geiger

Davi Geiger is an Associate Professor in the Department of Computer Science at New York University. His research interests include Computer Vision and Learning, with recent focus on Group and Quantum methods. He holds a Ph.D. in Physics and Artificial Intelligence from the Massachusetts Institute of Technology. Geiger is affiliated with the Courant Institute of Mathematical Sciences and is also involved in interdisciplinary work at the intersection of Computer Science and Neural Science. His academic profile includes contributions to machine learning and visual understanding, with an emphasis on uncovering underlying principles through advanced computational techniques.

Davi Geiger is a researcher at the Courant Institute, New York University, specializing in Artificial Intelligence and Computer Vision. His work focuses on developing algorithms for surface reconstruction, deformable shape analysis, and image segmentation. He has contributed to the understanding of occlusions, discontinuities, and epipolar lines in stereo vision, as well as methods for segmenting cardiac MR images using deformable models. His research also includes dynamic programming for tracking deformable contours and the use of MRFs (Markov Random Fields) for parallel and deterministic algorithms. Geiger's publications explore topics such as junction detection, shape similarity, and the integration of vision modules.