Matthew Nichols
Data Scientist
Washington DC-Baltimore Area United States
Summary
👤
Senior🎓
Top SchoolMatthew Nichols is a data scientist with a decade of experience applying advanced computational methods to real-world problems, currently building analytics and models at Fannie Mae. He brings a strong research pedigree from a PhD in Astronomy and Astrophysics and postdoctoral work at EPFL, where he developed highly efficient C algorithms for large-scale simulations and led international teams. Prior roles at HHMI blended software engineering and data science—designing image registration algorithms, scaling ML segmentation for petascale data, and managing hundreds of terabytes of research datasets. Matthew is comfortable moving models from research into production, with a track record of optimizing performance and storage costs by orders of magnitude. Colleagues describe him as the kind of scientist-engineer who pairs deep quantitative rigor with pragmatic engineering to deliver scalable, reproducible solutions.
11 years of coding experience
7 years of employment as a software developer
The University of Sydney
Github Skills (19)
image-filters9
dimensions9
image-data8
network-analysis7
neuroscience7
image-processing5
machine-learning4
python4
optical-flow4
computer-vision4
keras-neural-networks3
tiles3
image-annotation3
render2
rasterizer2
Programming languages (5)
Github contributions (5)
bocklab/temca2data
May 2017 - Mar 2019
Contributions:9 commits, 3 pushes, 1 branch in 1 year 10 months
public-codemachine-learning
JaneliaSciComp/fibsem-optflow
Feb 2019 - Nov 2019
Repository related to optical flow calculations for fibsem images
Contributions:2 PRs, 12 pushes, 1 comment in 9 months
opticaloptical-flowcalculations
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