Gary Tse
Clinical lead & cardiology domain expert
Shaping features that matter clinically: ECG interpretation, lead layout, and validation pathways.
Credits & Acknowledgments
Building Cardiodify with clinical focus, signal science, and on-device AI.
Our heritage: extensive experience across cardiology and computation -- from the Commodore 64 era to modern Android and on-device AI.
The Team
Mehrdad S. Beni
Computation & systems engineering
Signal pipeline, on-device AI integration, and performance—from byte-level parsing to UX.
Affiliation
Hong Kong Metropolitan University (HKMU), Hong Kong.
We collaborate across clinical research and engineering to keep Cardiodify practical, fast, and privacy-preserving.
Contributions
Android App
Modern, offline, and snappy—pinch-zoom ECG viewing with a clean clinical layout.
Signal Pipeline
Compact decode → LZW-style decompress → Δ-reconstruction → efficient plotting.
AI Detection
On-device R/S peak marking and lead-specific feature cues to speed interpretation.
Documentation & Website
Minimal, professional materials—easy to deploy on nginx with TLS (Let’s Encrypt).
Questions or collaboration ideas? Reach us via the project page on Cardiodify.