Paul Hendricks
Principal Solutions Architect at Franklin University
Columbus, Ohio, United States
Summary
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Rockstar🎓
Top SchoolPaul Hendricks is a Principal Solutions Architect at NVIDIA with 11 years of experience translating machine learning research into production-ready solutions and developer-focused tooling. Based in Columbus, Ohio, he has progressed through senior technical roles at NVIDIA after earlier data science and ML engineering positions at L Brands, Nexosis (acquired by DataRobot), and academic research at Ohio State. He actively contributes to open-source projects—most notably extending OpenAI Gym’s HTTP API with R and Julia bindings and improving cross-language serialization—demonstrating a knack for bridging ecosystems and languages. As an advisory board member for Franklin University’s MS in Data Analytics program, he combines industry practice with education, and his GitHub and Google Scholar presence reflect a blend of practical engineering and scholarly engagement.
11 years of coding experience
13 years of employment as a software developer
Bachelor's Degree, Mathematics, Statistics, Bachelor's Degree, Mathematics, Statistics at Ohio Wesleyan University
Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (18)
api-rest10
xgboost10
python10
apidoc10
api-design10
data-science10
restful-api10
openai-gym10
machine-learning10
cudf10
flask-ask10
rapids10
api10
rest-api10
jupyter-notebook10
Programming languages (12)
Github contributions (5)
rapidsai-community/notebooks-contrib
Mar 2019 - Jun 2019
RAPIDS Community Notebooks
Role in this project:
Data Scientist
Data ScientistContributions:48 commits, 16 PRs, 5 pushes in 2 months
Contributions summary:Paul contributed to the development of a notebook-based example utilizing the RAPIDS ecosystem within the context of the RAPIDS Community Notebooks. The commits involve modifications to existing notebooks, including changes in the code to reflect version updates and typo fixes. The changes suggest the user is working with data science and machine learning to illustrate various functionalities using cuDF and potentially Dask cuDF as well as XGBoost.
jupyter-notebooknotebooksrapids
openai/gym-http-api
Oct 2016 - Apr 2017
API to access OpenAI Gym from other languages via HTTP
Role in this project:Backend Developer
Backend DeveloperContributions:8 commits, 4 PRs, 5 comments in 5 months
Contributions summary:Paul contributed to the `openai/gym-http-api` repository by addressing a code style issue related to tabs and spaces within `gym_http_server.py`. They expanded the project's functionality by integrating R and Julia bindings, allowing users to interact with the OpenAI Gym API through these languages. Furthermore, the user modified the `env_reset` method to ensure the return value is a Python native type, impacting how data is serialized and exchanged via the API. The codebase also shows the user moving code between repositories.
apireinforcement-learningopenailanguagesgym
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