About Me
I’m an Assistant Professor of Computer Science at York University, a Faculty Affiliate at the Vector Institute and an Adjunct Professor in the University of Toronto Department of Computer Science. I am a member of the Centre for Vision Research and core member of the Vision: Science to Application (VISTA) program. I currently serve as an Associate Editor for IET Computer Vision and have been an Area Chair for a number of conferences.
I am also a Visiting Professor at Samsung AI Center - Toronto, a co-founder and advisor of Structura Biotechnology (makers of cryoSPARC) and an Academic Advisor at Borealis AI. Previously, I 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.
I studied at the University of Toronto where I received my PhD in 2011. I also did postdocs at the Toyota Technological Institute at Chicago and the University of Toronto. See my CV for more details.
Research Interests
I am interested in building rich, detailed models which capture fundamental relationships between the world and our observations of it. Such models ultimately enable us to measure and predict sometimes surprising details.
Most recently I have been focusing on generative models, specifically normalizing flows. My research has been exploring theoretical aspects of normalizing flows and their applications. I also have an interest on the problem of estimating the 3D structure of biological molecules such as proteins and viruses with Cryo-EM. Beyond those current focuses, I have also worked on vehicle localization for robotics, physically realistic models of human motion, probabilistic programming languages, Bayesian methods, MCMC and forensic ballistics.
Prospective Students
Interested in joining my group? I’m also on the look out for exceptional students and colleagues to work with. More information is available here.
Recent News
New Papers Now Available
The following new papers are now available:
- Noise2NoiseFlow: Realistic Camera Noise Modeling without Clean Images by Ali Maleky, Shayan Kousha, Michael S Brown, Marcus A Brubaker at CVPR 2022.
- Modeling sRGB Camera Noise with Normalizing Flows by Shayan Kousha, Ali Maleky, Michael S Brown, Marcus A Brubaker at CVPR 2022.
- Learning sRGB-to-Raw De-rendering with Content-Aware Metadata by Seonghyeon Nam and Abhijith Punnappurath and Marcus A. Brubaker and Michael S. Brown at CVPR 2022.
- Residual Multiplicative Filter Networks for Multiscale Reconstruction by Shayan Shekarforoush, David B Lindell, David J Fleet, Marcus A Brubaker on arXiv.
- Efficient CDF Approximations for Normalizing Flows by Chandramouli Shama Sastry, Andreas Lehrmann, Marcus Brubaker, Alexander Radovic on arXiv. Congratulations and thanks to my fantastic co-authors!
Papers accepted to CVPR 2022
Happy to announce three accepted papers at CVPR this year! They are currently not yet available but will be made available soon.
Paper accepted to AISTATS
Happy to announce another newly accepted paper. Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals by James A. Brofos, Marylou Gabrie, Marcus A. Brubaker and Roy R. Lederman will appear at AISTATS 2022. Congratulations to all my co-authors!
Papers accepted to NeurIPS and WACV
Happy to announce two newly accepted papers. Congratulations to all my co-authors!
- Continuous Latent Process Flows by Ruizhi Deng, Marcus A. Brubaker, Greg Mori and Andreas Lehrmann at NeurIPS 2021.
- Auto White-Balance Correction for Mixed-Illuminant Scenes by Mahmoud Afifi, Marcus A. Brubaker and Michael S. Brown at WACV 2022.
Senior Area Chair for AAAI 2022
I’m happy to announce that I’ll be serving as a Senior Area Chair for AAAI 2022.
Seminar at Amii
I will be giving a seminar about my work on normalizing flows on Friday at Amii. More information, including timing and registration, can be found here. Can’t make this one? There are several more seminars in the works for the next few months.
Awarded CFI Grant
I’m very happy to announce that my lab has been awarded a Canada Foundation for Innovation grant as part of the John R. Evans Leaders Fund. The grant, valued at $140,000CAD, will be used to purchase hardware to continue my groups research on generative models with a focus on applications in cryo-EM, hyperspectral imagery and video analysis.
New Preprint on arXiv
A new preprint is now available on arXiv!
- Neural Image Representations for Multi-Image Fusion and Layer Separation by Seonghyeon Nam, Mostafa Hussien, Marcus A. Brubaker and Michael S. Brown, preprint.
Recent Preprints and Workshop Papers on arXiv
Several new workshop papers and preprints are now available on arXiv!
- CAMS: Color-Aware Multi-Style Transfer by Mahmoud Afifi, Abdullah Abuolaim, Mostafa Hussien, Marcus A. Brubaker and Michael S. Brown, preprint.
- Continuous Latent Process Flows by Ruizhi Deng, Marcus A. Brubaker, Greg Mori and Andreas Lehrmann at ICML Workshop on Time Series, 2021.
- Manifold Density Estimation via Generalized Dequantization by James A. Brofos, Marcus A. Brubaker and Roy R. Lederman at ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, 2021.
- Zero-shot Learning with Class Description Regularization by Shayan Kousha and Marcus A. Brubaker at CVPR Workshop on Fine-Grained Visual Categorization, 2021.
Joining Samsung AI Toronto
I am excited to announce that I have joined the Toronto Samsung AI Center part time as a Visiting Professor. I will be overseeing projects in computer vision and machine learning with their excellent team of researchers. If you’re looking for an industrial position, be sure to check them out!
For more news see here.