Stephanie Ger
PhD Candidate
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolStephanie Ger is a PhD-trained applied mathematician and machine learning engineer with nine years of experience building production ML systems, from anomaly detection and time-series research to FaceID-scale data science at Apple. She combines deep theoretical grounding from Northwestern University with hands-on engineering—recently delivering end-to-end LLM and RAG-based recommendation models at NavOut AI. Her work spans neural interpretability and genomics to practical deployment, reflecting a rare fluency across research, product, and privacy-sensitive applications. Based in the Bay Area, she brings rigor and curiosity to high-impact problems, often translating mathematical insights into robust, interpretable models for real-world systems.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Arts (B.A.), Mathematics, Bachelor of Arts (B.A.), Mathematics at Boston CollegeDoctor of Philosophy (PhD), Applied Mathematics, 3.77, Doctor of Philosophy (PhD), Applied Mathematics, 3.77 at Northwestern UniversityUniversity College London
English, Chinese
Github Skills (5)
synthetic8
temporal8
classification7
temporal-data7
machine-learning5
Programming languages (1)
Github contributions (5)
stephanieger/imbalanced-sequence-classification
Jan 2019 - Aug 2020
Methods for generating synthetic minority data for multivariate temporal data to improve classification accuracy.
Contributions:12 commits, 3 PRs, 8 pushes in 1 year 7 months
accuracytemporal-datamachine-learningtemporalsynthetic
stephanieger/ConvectionalNN
May 2017 - Feb 2020
Contributions:20 pushes, 1 branch in 2 years 9 months
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