Ryan Cooper
Director Of Faculty Development at University of Connecticut
Mansfield, Connecticut, United States
Summary
👤
Senior🎓
Top SchoolRyan Cooper is a materials-focused engineering educator and researcher with 11 years of experience bridging academia, national lab research, and faculty development. With a PhD in Mechanical Engineering from Columbia, he has led experimental and computational studies in micro- and nanomechanics, additive manufacturing, and high-temperature alloys, and published in top journals while contributing code for digital image correlation and Monte Carlo fatigue models. As Director of Faculty Development at the University of Connecticut he coordinates faculty training, accreditation, and integrates AI and online course development across centers, while still teaching machine learning and finite element methods. He is an open-source-minded technical writer and educator who has contributed practical NumPy tutorials—e.g., demonstrating how to fit Moore’s Law from semiconductor data—highlighting his ability to turn complex data into reproducible learning resources. Colleagues value his knack for translating microscopy and microscopy-driven data into classroom-ready software and assessments. Based in Mansfield, CT, he combines hands-on lab skills with high-performance computing and pedagogy to advance both research and teaching.
11 years of coding experience
15 years of employment as a software developer
B.S., Mechanical Engineering and Mechanics, B.S., Mechanical Engineering and Mechanics at Drexel UniversityDoctor of Philosophy (PhD), Mechanical Engineering, Doctor of Philosophy (PhD), Mechanical Engineering at Columbia University - Fu Foundation School of Engineering and Applied Science
English
Github Skills (6)
user-manual10
learn-ruby-on-rails10
basics10
numpy10
linear-regression10
matplotlib9
Programming languages (9)
Github contributions (5)
numpy/numpy-tutorials
Sep 2020 - Aug 2021
NumPy tutorials & educational content in notebook format
Role in this project:
Data Scientist
Data ScientistContributions:30 reviews, 32 commits, 5 PRs in 11 months
Contributions summary:Ryan contributed a tutorial demonstrating how to apply linear regression using NumPy to determine Moore's Law based on semiconductor manufacturing data. Their commits focused on data loading from a CSV file, transforming the data, and fitting it to an exponential model. They also compared results from linear regression model to Moore's law and other fitting methods.
pythonnumpyjupyter-notebooknotebookdeep-learning
cooperorg/computational-mechanics
Aug 2022 - Dec 2024
nanohub compmech build materials
Contributions:2 PRs, 9 pushes in 2 years 4 months
falloer
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