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Rana Hanocka is an Assistant Professor in the Department of Computer Science at the University of Chicago. Her research interests lie at the intersection of computer graphics, machine learning, and computer vision. She focuses on developing artificial intelligence techniques to better understand and manipulate 3D geometric data. Her work includes designing deep learning architectures specifically for mesh data and exploring methods for effective surface reconstruction and texture synthesis. Hanocka aims to intertwine human creativity with machine-based processes to enhance 3D shape modeling and animation capabilities. She also investigates the interpretability of 3D neural networks and their applications in data-centric modeling and decision-making. Her research contributions have been recognized with several awards, including the 2023 Pazy Research Award and a 2025 Paper Honorable Mention at the 3DV conference. She completed her Ph.D. in 2021 at Tel Aviv University, where she was supervised by Daniel Cohen-Or and Raja Giryes. Hanocka leads the 3DL group at the University of Chicago, pursuing innovative research in 3D deep learning.
Department of Philosophy