Data scientist focusing on machine learning and predictive analytics. Currently, I work as a research scientist at Michigan Tech Research Institute, improving and implementing statistical methods for clients through developing scientific software, writing research proposals, creating and maintaining models, and wrangling new data sets. Previously, I was a computational scientist at the University of Illinois where I used numerical methods to expand the theory of computational plasmonics and was fortunate to be advised by David Nicholls. I also have experience with supercomputers and parallel processing at Argonne National Laboratory and finite element analysis at the Cold Regions Research and Engineering Laboratory. Prior to starting graduate school, I worked in Agile software development at Workforce Software and focused on data mining, numerical optimization, and software automation.
- Ann Arbor, MI
- https://matthewshawnkehoe.github.io/
- in/matthewshawnkehoe
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Data-Science-Machine-Learning-Collaborative-Learning-Group
Data-Science-Machine-Learning-Collaborative-Learning-Group PublicMaterial and projects from the Data Science & Machine Learning Collaborative Learning Meetup group
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Data-Science
Data-Science PublicA collection of Jupyter Notebooks highlighting data science and machine learning projects.
Jupyter Notebook 2
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HOPS-AWE-Grating-Scattering
HOPS-AWE-Grating-Scattering PublicA High–Order Perturbation of Surfaces/Asymptotic Waveform Evaluation (HOPS/AWE) algorithm for Grating Scattering Problems.
MATLAB 5
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Riemann-Zeta-Functions
Riemann-Zeta-Functions PublicComputer implementation of the Riemann Siegel formula in Julia alongside various plotting and numerical programs related to the Riemann zeta function.
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LevBahn/Gross-Pitaevskii-Eigenvalue-problem
LevBahn/Gross-Pitaevskii-Eigenvalue-problem PublicA project on Gross–Pitaevskii eigenvalue problem using Machine learning method
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Ann-Arbor-AI-ML-Group
Ann-Arbor-AI-ML-Group PublicMaterial and projects from the Ann Arbor AI/ML Meetup group
Jupyter Notebook 1
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