Emmy Zero is a computational physicist-turned-software practitioner with over a decade of experience modeling complex systems and publishing across epidemiology, statistical mechanics, biophysics, active matter, and dynamical systems. She holds a PhD in Physics from Penn State and has advanced the SciPy and Matplotlib ecosystems—improving numerical integration error handling and adding discrete-slider functionality—while hardening TextBlob’s NaiveBayes classifier for real-world text tasks. Based in Pittsburgh, Emmy blends hands-on research on nanoscale motor collective motion with practical engineering, including back-end contributions that improved performance, Python 3 compatibility, and documentation in major open-source projects. Outside academia she’s applied mechanical and teaching skills as a roller skate mechanic, sales associate, and instructor, a combination that highlights her pragmatic problem-solving and ability to communicate technical ideas to diverse audiences. An underappreciated detail: her GitHub activity shows a knack for addressing subtle edge cases and user-facing clarity, reflecting a researcher's attention to correctness applied to production libraries.
10 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Physics, Doctor of Philosophy (Ph.D.) Physics at Penn State University
Bachelor of Science - BS Physics, Bachelor of Science - BS Physics at Carnegie Mellon University
Contributions:8 commits, 4 PRs, 28 comments in 4 years 5 months
Contributions summary:Emmy primarily focused on improving the `scipy/scipy` library, specifically the `integrate` module. Their work involved enhancing the `quad` function by implementing a decision tree to provide clearer error messages for invalid inputs. Furthermore, the user performed code cleanup and PEP8 improvements, and modified documentation. The user also addressed a bug in the levy function.
Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
Role in this project:
Back-end Developer
Contributions:5 commits, 2 PRs, 7 comments in 8 months
Contributions summary:Emmy primarily focused on improving the `textblob` library's core functionality related to the `classifiers` module. They addressed performance issues in the `NaiveBayes` classifier by optimizing the feature extraction process and introduced a word set to track seen tokens. Several commits addressed edge cases such as empty training sets and Python 3 compatibility, ensuring the library's robustness. Finally, they updated a translation test case, reflecting the impact of changes in an external service.
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