Matthew Beveridge

PhD Student in Computational Imaging
Columbia University

beveridge [at] cs.columbia.edu

cv / google scholar / github / linkedin / twitter

Me

About

I am a first year PhD student at Columbia University in the Columbia Imaging and Vision Lab (CAVE) with Shree Nayar. My research is in computational imaging, with a focus on understanding the material properties of our lived environment. I'm interested in its relevance to robotics and remote sensing.

Prior to starting at Columbia, I completed my BS and MEng at MIT working with Daniela Rus on robot vision. I also worked on depth estimation at NODAR for a few years, and spent a summer at NASA.

News

[Jul 2023] I was awarded the Greenwoods Fellowship to support my studies at Columbia.

[Jun 2023] I joined Morteza Karimzadeh as a Visiting Researcher at CU Boulder to work on Arctic sea ice mapping from satellite imagery.

[May 2023] I received the LEAP Momentum Fellowship to study the optical properties of atmospheric aerosols. I will be working with Carl Vondrick and Kara Lamb. [press]

[Apr 2023] This Fall, I will be attending Columbia University to pursue a PhD with Shree Nayar.

[Oct 2022] A proposal for explainable forecasting of Arctic sea ice concentration was accepted to the NeurIPS 2022 Workshop on Tackling Climate Change with Machine Learning. [html]

[Sep 2022] Our work on motion tracking to identify and track turbulent filaments in fusion plasmas was accepted to Scientific Reports. [html] [press]

[Jan 2022] A paper on bayesian optimization of droplet generating hardware at varying scales was accepted to ACS Applied Materials and Interfaces. [html]

[Dec 2021] Two new papers accepted to the NeurIPS 2021 Workshop on Tackling Climate Change with Machine Learning on the topics of the Atlantic Multidecadal Variability [html] and biogeochemistry of the Southern Ocean [html]. The former was awarded best paper.

[Nov 2021] Generalizing Imaging through Scattering Media with Uncertainty Estimates was accepted to the WACV 2022 Workshop on Applications of Computational Imaging. [pdf]

[Aug 2021] Our work on using generative models to speed up computational fluid dynamics simulation, with application to urban wind modeling, was accepted to ACML 2021 for a long oral spotlight. [html]

[Jul 2021] Our paper on image-based audio augmentation was accepted to ICCV 2021. [html] I also began work as a Computer Vision Engineer at NODAR.

[May 2021] I completed my Master's thesis on consistent monocular depth estimation in data-driven simulation for reinforcement learning-based autonomous driving. [html]

Publications

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Last updated: June 5th, 2024. [source code]