Alexander Hayes
Visiting Lecturer at Indiana University Bloomington
Bloomington, Indiana, United States
Summary
🤩
Rockstar🎓
Top SchoolAlexander Hayes is a Visiting Lecturer and PhD candidate in Health Informatics at Indiana University with 11 years of experience bridging software engineering, data science, and teaching across the full stack. He develops production-ready Python packages and tooling—evidenced by refactoring and packaging work on the widely used arXiv LaTeX cleaner—and contributes maintenance and debugging utilities to ML libraries like imbalanced-learn. His research at IU focuses on precision health and predictive models for gestational diabetes, combining clinical goals with reproducible software practices. He has a strong background in teaching theoretical CS and practical programming, from automata theory to C and Unix, and a track record of shipping research software with tests and CI. Known for meticulous refactoring and documentation, he brings an uncommon emphasis on packaging, testability, and deployment to academic research code. Based in Bloomington, he blends open-source collaboration with applied health analytics to move research into usable tools.
11 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD Health Informatics, Doctor of Philosophy - PhD Health Informatics at Indiana University Bloomington
Stackoverflow
4,075reputation
164kreached
196answers
10questions
machine-learning
top-5%
scikit-learn
top-5%
python
top-5%
Github Skills (24)
python10
data-science10
scikit10
testing10
packaging10
machine-learning10
latex10
scikit-learn10
command-line-arguments9
numpy9
argument-parsing9
command-line-parser9
data-analysis9
unit-test8
unit-testing8
Programming languages (20)
Github contributions (5)
scikit-learn-contrib/imbalanced-learn
Mar 2019 - Dec 2022
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Role in this project:
Data Scientist
Data ScientistContributions:11 reviews, 6 commits, 11 PRs in 3 years 8 months
Contributions summary:Alexander primarily contributed to the project by adding and maintaining utility functions for debugging and system information. Their work involved implementing and updating a function to display system and dependency versions, including Python dependencies. Furthermore, they addressed typos in the documentation and made adjustments to test files to accommodate changes in the codebase, indicating a focus on maintenance and ensuring the project's robustness.
machine-learningpythonstatisticsdata-sciencedata-analysis
google-research/arxiv-latex-cleaner
Dec 2019 - Dec 2019
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
Role in this project:Back-end Developer
Back-end DeveloperContributions:8 commits, 1 PR, 4 comments in 1 day
Contributions summary:Alexander primarily focused on refactoring and packaging the arXiv LaTeX cleaner. They restructured the project into a Python package, moving code into a package directory, adding version information, and modifying import statements for tests. They also refactored the main module, introducing a public `run_arxiv_cleaner` method and integrating command-line argument parsing. The user's work streamlined the codebase and prepared the tool for broader use and distribution.
latexarxiv
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