Scholar
Michael Rubinstein
Google Scholar ID: ttBdcmsAAAAJ
Google DeepMind
Citations & Impact
Citations
12,221
H-index
41
i10-index
64
Publications
20
Co-authors
164
list available
Contact
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- SIGGRAPH 2023 Test-of-Time Award: 'Eulerian Video Magnification for Revealing Subtle Changes in the World' (SIGGRAPH 2012); CVPR 2023 Best Student Paper (Honorable Mention): 'DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation'; Associate Editor of SIAM Journal on Imaging Sciences (SIIMS); Area Chair for several conferences including CVPR 2020, ICCV 2021, ECCV 2022; Technical Papers Committee Member for SIGGRAPH 2019, 2020, 2022, SIGGRAPH Asia 2021, 2022, ICCP 2018, 2019, 2022; CVPR 2014 Best Demo Award: 'Real-time Video Magnification'; George M. Sprowls Award for outstanding doctoral thesis in Computer Science at MIT, 2014; Co-organized tutorial 'Dense Image Correspondences for Computer Vision' at ICCV 2013 and CVPR 2014; 2012 Microsoft Research PhD Fellowship (2012-2013); 2011 NVIDIA Graduate Fellowship.
Research Experience
- Principal Scientist / Director at Google DeepMind; previously a postdoctoral researcher at Microsoft Research New England.
Education
- PhD from MIT, supervised by Bill Freeman; spent a year as a postdoc at Microsoft Research New England before joining Google.
Background
- Research interests lie at the intersection of computer vision and computer graphics, particularly in low-level image/video processing and computational photography.
Miscellany
- Developed new methods to extract subtle motion and color signals from videos, which can be used to visualize blood perfusion, measure heart rate, and magnify tiny motions and changes we cannot normally see.
