Felix Heide
About Felix Heide
- Affiliations
- Princeton University, Princeton Computational Imaging Lab, _Professor
- Torc Robotics, Head of AI
- Location
- Princeton, New Jersey, United States of America
- Website
- https://www.cs.princeton.edu/~fheide/
- Bio
Excerpt from Wikipedia
Felix Heide is a German-born computer scientist known for his work in the fields of computational imaging, computer vision, computer graphics and deep learning. He is an assistant professor at Princeton University and was the head of the Computational Imaging Lab. He serves as Head of Artificial Intelligence at Torc Robotics. Heide co-founded Algolux, a startup in computer vision technology for self-driving vehicles, which later merged with Torc Robotics.
Heide completed his undergraduate and Master’s degree in computer science at the University of Siegen, where he graduated summa cum laude. In 2016, he received his PhD from the University of British Columbia under the advisement of Professor Wolfgang Heidrich. His doctoral dissertation won the Alain Fournier PhD Dissertation Award for the best Canadian PhD dissertation in computer graphics and the ACM SIGGRAPH outstanding doctoral dissertation award for the best PhD dissertation in computer graphics and interactive techniques. Following his doctoral studies, he conducted postdoctoral research at Stanford University, with visiting research stints at institutions including the Massachusetts Institute of Technology (MIT) and King Abdullah University of Science and Technology (KAUST).
SIGGRAPH Conference Organizing Committee Positions
- Committee Member
- SIGGRAPH Asia 2017: Technical Papers
- SIGGRAPH Asia 2016: Technical Papers
- SIGGRAPH Asia 2021: Technical Papers
- SIGGRAPH Asia 2022: Technical Papers
- SIGGRAPH Asia 2023: Technical Papers
- SIGGRAPH Asia 2024: Technical Papers
- Jury Member
- SIGGRAPH 2020: Technical Papers
Conference Contributions
- Experiences
-
Contributor(s):Entry #: 09 - Presentations
-
Presenter(s):Entry #: 114 - Sessions Moderated
- “Single Image Neural Material Relighting” by Bieron, Tong and Peers
- “Towards Material Digitization with a Dual-scale Optical System” by Garces, Arellano, Rodriguez-Pardo, Suja and Lopez-Moreno
- “Materialistic: Selecting Similar Materials in Images” by Sharma, Philip, Gharbi, Freeman, Durand, et al. …
- “End-to-end Procedural Material Capture with Proxy-Free Mixed-Integer Optimization” by Li, Matusik and Shi
- “Neural Biplane Representation for BTF Rendering and Acquisition” by Fan, Wang, Hasan, Yang and Yan
- “Ultra-high Resolution SVBRDF Recovery From a Single Image” by Guo, Lai, Tu, Tao, Zou, et al. …
Other Information
- Roles
- Awardee
- Course Presenter
- Emerging Technologies Presenter
- Posters Jury Member
- Technical Paper Moderator
- Technical Paper Presenter
- Technical Papers Jury Member
- Technical Papers Organizing Committee Member
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