Dorota Jarecka
Research Scientist at Massachusetts Institute of Technology
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolDorota Jarecka is a research scientist in Cambridge, MA with 14 years of experience applying physics, numerical methods, and software engineering to atmospheric and neuroimaging problems. She combines a PhD in Atmospheric Physics with strong analytical and programming skills, repeatedly optimizing scientific code (e.g., speeding Python/NumPy implementations and reducing memory by 50%) and binding C++ schemes into legacy workflows. At MIT she leads reproducible science and machine learning efforts while contributing to major open-source projects like nipy/nipype and nibabel, where she focused on backend development and migrating tests to pytest to improve reliability. Known as a collaborative organizer and effective team player, she also brings practical QA and test automation expertise that bridges research and production-ready software.
14 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Atmospheric Physics, Doctor of Philosophy (Ph.D.), Atmospheric Physics at University of WarsawPyLadies
English, Polish
Github Skills (11)
testing10
pytest10
python10
neuroimaging10
brain-imaging10
numpy9
dataflow7
dataflow-programming7
workflow-engine7
data-formats5
data-format5
Programming languages (21)
Github contributions (5)
nipy/nipype
Oct 2016 - Sep 2022
Workflows and interfaces for neuroimaging packages
Role in this project:
Back-end Developer & QA Engineer / Test Automation Engineer
Back-end Developer & QA Engineer / Test Automation EngineerContributions:250 commits, 67 PRs, 2 branches in 6 years
Contributions summary:Dorota primarily focused on the improvement and testing of the `nipype/nipype` repository. They made various code changes, including adding inputs, output types and testing changes within auto tests and base tests. They also addressed issues, such as converting from nose library to pytest.
workflowneuroimagingpythondata-scienceworkflow-engine
nipy/nibabel
Nov 2019 - Feb 2020
Python package to access a cacophony of neuro-imaging file formats
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:3 reviews, 105 commits, 5 PRs in 3 months
Contributions summary:Dorota primarily focused on converting existing tests to the pytest framework. This involved rewriting test cases, modifying test files, and adjusting import statements to align with pytest. The user also added a testing utility module and addressed issues related to test setup and execution within the project's testing framework, improving the overall testing infrastructure. This work contributes to enhancing the project's testability and reliability.
pythontckimagingtrkstreamlines
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