Davi Geiger

Davi Geiger is an Associate Professor of Computer Science and Neural Science at New York University (NYU), affiliated with the Courant Institute of Mathematical Sciences. He is part of the Computer Vision Group within the College of Arts and Science and the Graduate School of Arts and Science. His research focuses on advancing computer vision and machine learning, with a recent emphasis on integrating quantum methods and group theory. His work explores topics such as stereo vision, human perception modeling, quantum entropy, and medical imaging analysis.

Key research areas include quantum algorithms applied to vision problems, geometric constraints in stereo matching, and entropy-based models in physics. Notable contributions include studies on cyclopean stereo vision, spin entropy dynamics, and regularization techniques for image classification. Dr. Geiger has led projects funded by grants such as the NSF's 'Geometry-and Symmetry-Driven Computer Vision Methods for High-Throughput Automated Microscopic Imaging.' His work bridges theoretical physics and computational methods, with applications in medical imaging and developmental biology.

Scientific achievements include pioneering methods for cell division detection in embryo development and developing adaptive confusion energy models for natural data distribution. His research often combines interdisciplinary approaches, leveraging insights from neuroscience and quantum computing to solve complex vision problems.