Swiss educated and Stanford trained AI and digital health researcher with 10+ years of experience building AI and software systems for health applications across academia and industry, including 2 years as technical lead, and 6+ years specializing in remote health sensing leveraging large-scale (multi-terabyte) datasets. Currently a postdoctoral researcher at Stanford University working on wearable foundation models and video agents. Track record includes 30+ published research articles (700+ citations), EU and US patent filings, and USD 300,000+ in competitive awards and fellowships.
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Stanford University
- California
- www.linkedin.com/in/narayan-schuetz
Highlights
- Pro
Pinned Loading
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SpectralLayersPyTorch
SpectralLayersPyTorch PublicTrainable linear spectral layers for PyTorch
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biobankAccelerometerAnalysis
biobankAccelerometerAnalysis PublicForked from OxWearables/biobankAccelerometerAnalysis
Extracting meaningful health information from large accelerometer datasets
Java
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DeepDIVA
DeepDIVA PublicForked from DIVA-DIA/DeepDIVA
Python Framework for Reproducible Deep Learning Experiments
Python 1
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ax3_accelerometer_pipeline
ax3_accelerometer_pipeline PublicProvides functionality to build flexible feature extraction pipelines based on raw Axivity AX3 3-axis accelerometer signals.
Python
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edf2parquet
edf2parquet PublicSimple utility package to convert EDF/EDF+ files into Apache Parquet format.
Jupyter Notebook 2
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