Kyra Swanson

Research Coordinator

San Diego, California, United States
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Summary

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Senior
🎓
Top School
Kyra Swanson is a Research Coordinator and computational neuroscientist with 11 years of programming experience focused on reinforcement learning and machine learning. With a PhD in Neuroscience and a BS in Computer Science, she bridges biological decision-making and algorithmic models to tackle real-world conservation problems. Currently applying ML to field-driven initiatives at the San Diego Zoo Wildlife Alliance, she translates complex research into deployable tools for wildlife protection. Her background includes a postdoctoral fellowship at the Smithsonian National Zoo, reflecting hands-on experience in both lab and applied conservation settings. Driven by a commitment to help the planet in crisis, she blends rigorous experimental science with practical software skills to deliver impact. A detail that often surprises collaborators: she pairs deep theoretical insight into decision mechanisms with decade-plus software craftsmanship, enabling both novel experiments and production-ready solutions.
code11 years of coding experience
bookDoctor of Philosophy - PhD, Neuroscience, Doctor of Philosophy - PhD, Neuroscience at American University
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Github Skills (11)

machine-learning9
deep-learning9
sqlite-extension9
python7
sqlite7
polar5
observation4
activity-recognition3
vector-search3
responsive3
logging2

Programming languages (4)

RC++CPython

Github contributions (5)

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conservationtechlab/animl-r

Dec 2021 - Jan 2023

Animl comprises a variety of machine learning tools for analyzing ecological data. The package includes a set of functions to classify subjects within camera trap field data and can handle both images and videos.
Contributions:3 releases, 23 reviews, 108 commits in 1 year 1 month
machine-learningdeep-learning
conservationtechlab/animl-py

Mar 2023 - Jul 2026

Animl comprises a variety of machine learning tools for analyzing ecological data. This Python package includes a set of functions to classify subjects within camera trap field data and can handle both images and videos.
Contributions:6 releases, 29 reviews, 144 PRs in 3 years 4 months
machine-learningpython
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