Gene Callahan
Adjunct Professor at New York University
Columbia, South Carolina, United States
Summary
👤
Senior🎓
Top SchoolGene Callahan is an adjunct professor and software engineer with three decades of software development experience and over a decade teaching at NYU Tandon, where he covers DevOps, algorithms, discrete math and operating systems. He blends academic rigor—holding a PhD in political theory and an MSc from LSE—with hands-on Python engineering, contributing core grid and neighbor-search logic to the well-known Mesa agent-based modeling library. His background spans industry and consultancy roles dating back to the 1980s, from building turnkey systems to leading agent-based modeling projects at Indra's Net. A careful technical communicator, he has also improved matplotlib documentation and routinely translates complex modeling concepts into teachable code and curricula. Based in Columbia, SC, he balances research, classroom instruction, and open-source development, often resurfacing academic insights in practical simulation tools.
11 years of coding experience
15 years of employment as a software developer
PhD Political Theory, PhD Political Theory at Cardiff University / Prifysgol CaerdyddLondon School of Economics and Political Science
Italian, Spanish, French, German
Github Skills (12)
simulations10
data-visualizations10
simulation10
data-visualization10
data-visualisation10
agent-based-modeling10
python10
plot10
documentation10
iterator9
refactoring8
simulation-framework7
Programming languages (7)
Github contributions (5)
projectmesa/mesa
Mar 2015 - Mar 2015
Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 commits, 2 PRs, 11 comments in 27 days
Contributions summary:Gene primarily contributed to the core logic of the Mesa agent-based modeling library. Their work involved implementing and refactoring grid-related functionalities, including iterators and neighbor searches within the spatial environment. The user also integrated these new grid functions into existing example models, such as the Schelling model, improving the overall structure and performance of the library. These changes suggest a focus on improving the foundational components of the modeling environment.
complex-systemsmodeling-agentspythonagent-basedagent
matplotlib/matplotlib
Sep 2015 - Oct 2015
matplotlib: plotting with Python
Role in this project:Technical Writer
Technical WriterContributions:7 commits, 2 PRs, 2 comments in 13 days
Contributions summary:Gene primarily contributed to the project's documentation, focusing on the pyplot tutorial and navigation toolbar documentation. Their work involved minor textual cleanup, adding specific details, and clarifying existing explanations. The commits demonstrate an understanding of the documentation's structure and content, with a focus on improving clarity and accuracy.
pythondata-sciencegtkdata-visualizationplotting
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