Vincent Sitzmann
Assistant Professor at Massachusetts Institute of Technology
Cambridge, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolVincent Sitzmann is an Assistant Professor at MIT CSAIL and founder-focused researcher who develops neural scene representations that let machines infer geometry, materials, and lighting from sparse visual observations. With an 11-year track record spanning a Stanford PhD, postdoc work with leading vision labs, and industry stints including Google AI and a startup (Yellow), he bridges deep learning, optimization, and multi-view/projective geometry to push practical 3D reconstruction and novel view synthesis. He leads the Scene Representation Group to enable agents that can reason and act in visual environments and also explores end-to-end camera optimization for task-specific sensors. His background in entrepreneurship and product-oriented roles means he translates cutting-edge research into tools for digital-world creators as well as academic impact. Based in Cambridge, MA, he combines self-supervised learning instincts with hardware-aware design—seeking to make perception systems learn and sense more like humans.
11 years of coding experience
5 years of employment as a software developer
Honours Degree in Technology Management, Technology Management, Honours Degree in Technology Management, Technology Management at Center for Digital Technology and Management (CDTM)Hong Kong University of Science and Technology (HKUST)Bachelor of Science - BS, Electrical Engineering, Bachelor of Science - BS, Electrical Engineering at Technical University of MunichDoctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at Stanford University
German, English, French, Chinese
Github Skills (21)
periodic10
3d-structure10
representations10
implicit10
scene10
self-organizing-map10
downsampling9
sane9
upsampling9
activation9
deep-learning8
machine-learning8
pytorch7
tensorflow7
automatic-differentiation7
Programming languages (3)
Github contributions (5)
vsitzmann/awesome-implicit-representations
Dec 2020 - Dec 2021
A curated list of resources on implicit neural representations.
Contributions:14 commits, 1 PR, 9 pushes in 11 months
implicitrepresentationsdeep-learningneural-networksmachine-learning
vsitzmann/light-field-networks
Jul 2021 - Dec 2021
Contributions:8 commits, 3 pushes, 1 comment in 5 months
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