Felix Heide

Felix Heide is an Assistant Professor in the Department of Computer Science at Princeton University. His research focuses on computational imaging and computer vision systems, integrating optics, machine learning, optimization, computer graphics, and computer vision. He has co-authored over 30 publications and filed 6 patents. He received his Ph.D. from the University of British Columbia under Professor Wolfgang Heidrich and has held positions at the University of Siegen and Stanford University. His doctoral dissertation earned the Alain Fournier Ph.D. Dissertation Award and the SIGGRAPH outstanding doctoral dissertation award. He is affiliated with the Princeton Computational Imaging Lab.

Felix Heide is a researcher at Princeton University with a focus on computational imaging, computer vision, and deep learning. His work explores advanced techniques for improving image quality and perception in challenging environments. Heide's research includes deep multimodal sensor fusion for adverse weather conditions, neural scene graphs for dynamic scenes, and computational imaging through simple lenses. His publications also address topics such as non-line-of-sight detection, hyperspectral imaging, and optical metasurfaces. Heide's contributions span both theoretical and applied aspects of imaging systems, with an emphasis on real-time and high-resolution imaging solutions.