Here are some of the projects I've worked on, spanning machine learning, wearable sensing, digital health, and graph neural networks. Each project represents my exploration of how AI can help us understand human health and behavior.
AI-Driven Light Exposure Classification
Machine learning framework for classifying light exposure patterns from wearable spectral sensors. Achieved AUC≈0.93 using participant-wise cross-validation with α-opic metrics and spectral power distribution features.
PrimeKG-RGCN Link Prediction
Graph neural network implementation for link prediction on PrimeKG, a large-scale biomedical knowledge graph. Explored R-GCN architectures to predict missing relationships between diseases, drugs, and biological entities.
Interested in Collaboration?
I'm always open to discussing new projects, research ideas, or partnership opportunities in the areas of digital health, wearable sensing, and machine learning.
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