Emily Ruzich
Clinical Outcomes Assessment (COA) Lead at Sanofi
Greater Boston United States
Summary
👤
Senior🎓
Top SchoolEmily Ruzich is a PhD-trained clinical neuroscience researcher and COA lead with 15 years of experience translating neuroimaging and patient-experience science into regulatory-grade evidence and communications. She has led patient-centered outcomes strategy and dossier development at IQVIA and now guides COA work at Sanofi, combining deep EEG/MEG technical expertise with pragmatic regulatory writing. Emily’s background spans academic neuroimaging (Harvard/MIT, Cambridge) and patient-facing market access writing, making her equally fluent in complex data analytics and clear, patient-centered narratives. An open-source technical writer for the widely used MNE-Python project, she has a track record of improving scientific documentation so users can apply advanced neurophysiology tools more effectively.
15 years of coding experience
8 years of employment as a software developer
Experimental Psychology and Physiology, Experimental Psychology and Physiology at University of OxfordDoctor of Philosophy (PhD), Doctor of Philosophy (PhD) at University of CambridgeB.S. with Honors, summa cum laude, Biology, Neuroscience, Anthropology, B.S. with Honors, summa cum laude, Biology, Neuroscience, Anthropology at University of Richmond
English, French
Github Skills (11)
rs10
restructuredtext10
documentation10
neuroscience5
el4
ceph4
ec4
neuroimaging4
mage4
ereg4
python3
Programming languages (1)
Github contributions (1)
mne-tools/mne-python
Mar 2011 - Jun 2011
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Role in this project:
Technical Writer
Technical WriterContributions:41 commits in 2 months
Contributions summary:Emily's contributions focused entirely on fixing and refining the manual documentation for the MNE-Python library. The commits consistently address issues within the documentation files, including correcting cross-references, updating links, and improving the clarity and accuracy of explanations. The user's work primarily involves editing and updating reStructuredText (RST) files related to various aspects of the MNE-Python library, ensuring comprehensive and accurate documentation for end users.
visualizationneuroimagingneurosciencepythonstatistics
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