Scholar
Marcus A Brubaker
Google Scholar ID: x2wyjkAAAAAJ
Research Scientist, Google DeepMind; Associate Prof, York University; Affiliate, Vector Institute
Citations & Impact
Citations
20,654
H-index
29
i10-index
45
Publications
20
Co-authors
112
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Served as an Associate Editor for IET Computer Vision and as an Area Chair or Senior Area Chair for several conferences including CVPR, ECCV, NeurIPS, and AAAI. Recently, two papers were accepted at ICCV 2023: 'Reference-guided Controllable Inpainting of Neural Radiance Fields' and 'Long-Term Photometric Consistent Novel View Synthesis with Diffusion Models'.
Research Experience
- Currently a Research Scientist at Google DeepMind, an Associate Professor at York University, the founder and director of the Computational Vision and Imaging Lab at York, a Visiting Professor at Samsung AI Center - Toronto, a co-founder and advisor of Structura Biotechnology, and an Academic Advisor at Borealis AI. Previously, he was a Research Director (2018-2020) at Borealis AI, a Research Associate at Cadre Research Labs (makers of TopMatch-GS), and one of the original contributors to Stan.
Education
- Received his PhD from the University of Toronto in 2011. Conducted postdoctoral research at the Toyota Technological Institute at Chicago and the University of Toronto.
Background
- Interested in Computer Vision, Machine Learning, Statistics and their application to a range of problems. Currently, he is a Research Scientist at Google DeepMind, an Associate Professor of Computer Science at York University, a founder and director of the Computational Vision and Imaging Lab at York, a Faculty Affiliate at the Vector Institute, and an Adjunct Professor in the University of Toronto Department of Computer Science. He is a member of the Centre for Vision Research and a core member of the Vision: Science to Application (VISTA) program.
Miscellany
- Interests include generative models (specifically normalizing flows), estimating the 3D structure of biological molecules such as proteins and viruses with Cryo-EM, vehicle localization, physically realistic models of human motion, probabilistic programming languages, Bayesian methods, MCMC, and forensic ballistics.
