Senior Scientific Software Engineer at Harvard John A. Paulson School of Engineering and Applied Sciences
Cambridge, Massachusetts, United States
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Summary
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Melissa Sulprizio is a Senior Scientific Software Engineer with 15 years of experience building and maintaining scientific models and tooling, currently supporting GEOS-Chem at Harvard SEAS. She specializes in Fortran-based atmospheric chemistry and aerosol code, Unix-based workflows, and reproducible model runs, and routinely applies Python, Perl, shell scripting, and Git to production research code. Her work includes backend contributions to the widely used geoschem/geos-chem science codebase—fixing algorithms for aerosol dry deposition and improving data module interfaces—helping an international user community run and trust complex simulations. Comfortable translating research into robust software, she also maintains user documentation and provides community support, a role that blends hands-on debugging with scientific communication. Her background in meteorology and atmospheric science gives her domain fluency that accelerates development and validation of large-scale Earth system modeling.
15 years of coding experience
12 years of employment as a software developer
B.S., Meteorology, B.S., Meteorology at Plymouth State University
M.S., Atmospheric Science, M.S., Atmospheric Science at State University of New York at Albany
GEOS-Chem "Science Codebase" repository. Contains GEOS-Chem science routines, run directory generation scripts, and interface code. This repository is used as a submodule within the GCClassic and GCHP wrappers, as well as in other modeling contexts (external ESMs).
Role in this project:
Backend Developer
Contributions:32 releases, 447 reviews, 1649 commits in 9 years 6 months
Contributions summary:Melissa made multiple commits to the `geoschem/geos-chem` repository, with changes primarily focusing on the Fortran source code within the Aerosol and Chemistry modules. The commits include modifications to algorithms for aerosol dry deposition, including adjustments for new data and error correction. The user also improved the use of different modules that provide data to the core model.
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Melissa Sulprizio - Senior Scientific Software Engineer at Harvard John A. Paulson School of Engineering and Applied Sciences