Vincent Sitzmann
Vincent Sitzmann
Massachusetts Institute of Technology
Names
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Emails
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****@cs.stanford.edu
, ****@stanford.edu
, ****@mit.edu
Personal Links
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Education & Career History
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Assistant Professor
Massachusetts Institute of Technology (mit.edu)
2022 – Present
Postdoc
Massachusetts Institute of Technology (mit.edu)
2020 – 2022
Academic Advisor
Preferred Networks, Inc. (preferred.jp)
2020 – 2021
PhD student
Stanford University (stanford.edu)
2017 – 2020
MS student
Stanford University (stanford.edu)
2015 – 2017
Undergrad student
Technical University Munich (tum.de)
2011 – 2015
Advisors, Relations & Conflicts
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Postdoc Advisor
Joshua Tenenbaum
****@mit.edu
2020 – Present
Coauthor
Yilun Du
****@mit.edu
2020 – Present
Coauthor
Anthony Simeonov
****@mit.edu
2020 – Present
Coauthor
Andrea Tagliasacchi
****@google.com
2020 – Present
Coauthor
Prafull Sharma
****@mit.edu
2020 – Present
Coauthor
Daniel Rebain
****@gmail.com
2020 – Present
Coauthor
Ke Li
****@sfu.ca
2020 – Present
Coauthor
David Lindell
****@stanford.edu
2020 – Present
Coauthor
Julien Martel
****@stanford.edu
2020 – Present
Coauthor
Alexander Bergman
****@stanford.edu
2020 – Present
Coworker
Tuan Anh Le
****@mit.edu
2020 – Present
Coauthor
Noah Snavely
****@google.com
2019 – Present
Coauthor
Christian Theobalt
****@mpi-inf.mpg.de
2019 – Present
Coauthor
Kyaw Zaw Lin
****@comp.nus.edu.sg
2019 – Present
Postdoc Advisor
Fredo Durand
****@mit.edu
2019 – Present
Postdoc Advisor
William Freeman
****@mit.edu
2019 – Present
Coauthor
Eric Ryan Chan
****@stanford.edu
2019 – Present
Coauthor
Jiajun Wu
****@stanford.edu
2019 – Present
PhD Advisor
Gordon Wetzstein
****@stanford.edu
2017 – Present
Coauthor
Matthias Niessner
****@tum.de
2018 – 2019
Coauthor
Justus Thies
****@tum.de
2018 – 2019
Coauthor
Michael Zollhöfer
****@fb.com
2018 – 2019
Coauthor
Felix Heide
****@cs.princeton.edu
2017 – 2019
Expertise
For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing
meta-learning
2019 – Present
3D Computer Vision
2017 – Present
neural scene representations
2017 – Present
neural rendering
2017 – Present
differentiable rendering
2017 – Present
representation learning
2017 – Present