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Decoding Brain Activity at Scale
Team-led neuroscience pipelines and algorithms for massive calcium imaging datasets.
The problem
Harvard Medical School and FORTH needed to analyze communication patterns in neuronal activity.
The dataset scale was extreme: 10,000+ neurons generating 80GB+ of calcium imaging data.
What I built / changed
- Led an 8-person data science team.
- Built preprocessing pipelines and analysis tooling.
- Developed ML algorithms for pattern detection.
- Built visualization tools for researchers.
- Applied statistical multivariate analysis and neural networks to extract insights.
Result
Published research on spontaneous brain activity patterns.
Stack / concepts
Big DataMLNeural networksResearch
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