Regular biography
David Fouhey is an Associate Professor in the Department of Electrical Engineering at New York University. His research interests include computer vision, machine learning, deep learning, AI for science, and robotics. Fouhey's work has contributed to advancements in AI-driven systems for biological research, such as the development of Skelevision, a computer vision system used to analyze bird skeletons. He has held positions at the University of Michigan and INRIA Paris, and his research has been recognized through various awards and grants. Fouhey's academic profile can be accessed at cs.nyu.edu/~fouhey.
Scholar-generated biography
David Fouhey is a researcher at New York University with expertise in Computer Vision, Machine Learning, AI for Science, and Solar Physics. His work focuses on developing deep learning methods for 3D understanding, object representation, and visual grounding. He has published on topics such as surface normal estimation, hand reconstruction, and AI applications in medical diagnosis. His research also includes data-driven approaches for 3D scene understanding and the creation of machine learning datasets from scientific missions like NASA's Solar Dynamics Observatory. Fouhey's contributions span both fundamental computer vision challenges and real-world applications in healthcare and scientific domains.