Corey Lynch
Director Of AI at Figure
Honolulu, Hawaii, United States
Summary
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RockstarCorey Lynch is a Director of AI with 14 years of experience building and scaling robotics and machine learning systems, currently leading AI at Figure after a senior research scientist stint at Google Brain. He blends deep research chops in robotics with hands-on engineering—evidenced by contributions to scikit-learn and a Python factorization machines implementation—so he navigates both algorithm design and production code. Based in Honolulu, he has driven robot manipulation teams and advanced learning algorithms that bridge research prototypes to deployed systems. Notably, his open-source work shows attention to both mathematical fidelity and practical compatibility, reflecting a pragmatic researcher-engineer approach.
14 years of coding experience
10 years of employment as a software developer
Github Skills (23)
algorithm10
factoring10
sgd10
2factor10
gd10
python10
scikit10
machine-learning10
machine-learning-algorithms10
factors10
scikit-learn10
factorization10
data-analysis10
matplotlib9
lib9
Programming languages (3)
Github contributions (5)
coreylynch/pyFM
Dec 2012 - Apr 2018
Factorization machines in python
Role in this project:
Back-end Developer / ML Engineer
Back-end Developer / ML EngineerContributions:28 commits, 9 PRs, 10 pushes in 5 years 4 months
Contributions summary:Corey contributed significantly to the `pyfm` repository, which focuses on Factorization Machines in Python. Their commits primarily involve modifications to core FM model components (`fm_model_new.h`), and SGD-based learning mechanisms (`fm_learn_sgd_element_new.h`). They also introduced compatibility features, demonstrating a focus on the underlying mathematical model and its implementation, alongside setup modifications.
pythonfactorizationmachinesfactorization-machinesmachine-learning
scikit-learn/scikit-learn
Oct 2012 - Nov 2012
scikit-learn: machine learning in Python
Role in this project:Data Scientist
Data ScientistContributions:10 commits in 7 days
Contributions summary:Corey made several contributions focused on improving an example within the scikit-learn library. They primarily edited a cross-validation digits example, modifying parameters, kernels, and plotting features. Their work involved adjusting the visualization to improve clarity, with specific changes to y-axis ticks and the range of C values. Additionally, the user's commits included Cythonization of a core function in a different part of the library.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
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