Matthew Cornell
Senior Research Software Enginner at Self-Employed
Amherst, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolMatthew Cornell is a seasoned senior research software engineer with over two decades of experience building production-grade systems across desktop, web, and cluster environments, currently focused on biostatistics and infectious disease forecasting at UMass Amherst. He architects and implements end-to-end solutions—APIs, data pipelines, databases, visualizations, and scalable web apps—most recently building and scaling the Django/Postgres-based Zoltar forecasting repository to hundreds of millions of rows. Language-agnostic and pragmatic, he programs primarily in Python but brings deep experience in Java, Scala, JavaScript, and SQL, and has written compilers, simulators, ML algorithms, and authoring tools. A longtime advocate of engineering discipline, he has coached teams in Extreme Programming, instituted CI and robust development practices, and saved operations costs through thoughtful infrastructure consolidation. Beyond hands-on engineering he pursues creative research and public-facing projects—from an NLP skeptical toolbox to a weather web app—and has published professionally, blending rigorous academic thinking with practical production delivery.
11 years of coding experience
19 years of employment as a software developer
University of Massachusetts AmherstBachelor's Degree, Electrical Engineering, Bachelor's Degree, Electrical Engineering at Bradley University
Stackoverflow
4,134reputation
574kreached
34answers
33questions
unit-testing
top-5%
Github Skills (154)
standardized10
forecast10
forecasts10
data-access10
atmospheric-modelling10
bootstrapping10
analytics10
visualization10
plot9
django-rest9
api9
envfile9
rest-framework9
qunit9
unit-testing9
Programming languages (10)
Github contributions (5)
hubverse-org/hub-dashboard-predtimechart
Aug 2024 - Apr 2025
An initial dashboard that provides a predtimechart-based forecast visualization component for the hub.
Contributions:30 reviews, 37 PRs, 30 pushes in 7 months
reichlab/covidModels
Jan 2022 - Jan 2024
predictive models for covid
Contributions:1 review, 13 PRs, 92 pushes in 1 year 11 months
predictivepredictive-modelspythonmachine-learning
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