Assistant Professor, Canada CIFAR AI Chair at University of Alberta
Edmonton, Alberta, Canada
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Abby Azari is an Assistant Professor and Canada CIFAR AI Chair at the University of Alberta who blends probabilistic machine learning with planetary and space physics to extract scientific understanding from large, noisy datasets. With eight years of research and teaching experience and a PhD in Atmospheric, Oceanic and Space Science from the University of Michigan, she leads the Azari Research Group and advances uncertainty quantification and interpretable ML for planetary systems. A NASA MAVEN science team member and former postdoc at Berkeley and UBC, she has applied Gaussian processes and Bayesian methods to planetary magnetism and space physics. Abby’s work sits at an unusual intersection of academia and mission science, translating ML innovations directly into tools used for spacecraft data analysis.
8 years of coding experience
5 years of employment as a software developer
BA Physics Minor Astronomy, BA Physics Minor Astronomy at Smith College
Doctor of Philosophy (PhD) Atmospheric Oceanic and Space Science, Doctor of Philosophy (PhD) Atmospheric Oceanic and Space Science at University of Michigan College of Engineering
This repository contains the laboratory portion of an upper level undergraduate class in Python on data visualization and statistics for geo & space scientists. Labs are updated when the course is in session through the most recent branch. See master version for current class.
Contributions:349 commits, 4 PRs, 340 pushes in 2 years 8 months
scientistspythongeolaboratoryundergraduate
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