EpiCast

Multi-Modal AI Epidemiological Surveillance System

Built a mobile-first disease surveillance platform for West Africa (ECOWAS) combining fine-tuned medical LLMs with audio AI for syndromic monitoring and cough-based respiratory illness detection.

Fine-tuned and quantized MedGemma 4B to GGUF format for on-device inference, enabling a complete offline AI stack on mobile devices with sub-second response times and zero cloud dependency.

Integrated MedGemma SigLIP for clinical image triage, HeAR audio models for cough classification, and a multilingual NLP pipeline trained on 3,400+ corpus-grounded examples across French, Hausa, and Yoruba.

Designed a 4-tab mobile interface (Dashboard, Intake, Alerts, Reports) with real-time syndromic heatmaps and automated situation report generation using MedGemma 27B.

Tech Stack: MedGemma 4B/27B, MedGemma SigLIP, Google HeAR, FastAPI, RunPod Serverless, Python