David Masad is an interdisciplinary research scientist with 13 years of experience applying quantitative methods and large-scale data to complex social science and policy questions. He combines agent-based simulations, network analysis, statistical modeling, and text processing to rapidly turn messy social data into actionable insights. A core back-end contributor to the widely used Mesa Python library, he has built foundational classes, spatial components, schedulers, and text visualizations that enable reproducible simulations of emergent behavior. Based in Virginia, he bridges academic rigor from George Mason University with practical open-source engineering, favoring tools that scale from research prototypes to policy-relevant analysis.
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
Contributions:316 commits, 148 PRs, 309 pushes in 7 years 2 months
Contributions summary:David primarily focused on developing and implementing core features for the Mesa agent-based modeling library. Their contributions involved creating fundamental classes such as Model, Agent, and Grid, which form the basis for constructing models. The user also created a scheduler to manage agent activation and implemented various spatial components. Furthermore, the user built text-based visualizations.
A simple parameterized storylet manager for Twine and Sugarcube
Contributions:39 commits, 6 PRs, 17 pushes in 1 month
parameterizedtwinesugarcube
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David Masad - Research Scientist at George Mason University