Biometric Systems
Redefining identity for the decentralised era — privacy-first recognition systems that never expose biometric templates to a central server.
Biometric Systems
Our biometric research develops advanced multimodal recognition systems using facial, fingerprint, iris, and behavioural biometrics. We prioritise security, privacy preservation, and ethical implementation — using zero-knowledge proofs and federated architectures to ensure biometric data never leaves the device.
Key Research Topics
Multimodal Recognition
Fusing fingerprint, facial, and iris modalities for robust recognition under degraded conditions and partial occlusion.
Iris & Retinal Analysis
Deep learning pipelines for high-resolution iris and retinal biometrics, including analysis under low-light and off-angle conditions.
Privacy-First Architectures
Zero-knowledge proof protocols and homomorphic encryption schemes that verify identity without ever exposing raw templates.
Spoofing & Liveness Detection
Adversarial presentation-attack detection models trained on synthetic and real spoofing datasets to harden recognition pipelines.
Current Projects
ZKBio: Zero-Knowledge Biometric Authentication
Privacy-preserving biometric authentication using zero-knowledge proofs — securing identity without exposing raw biometric data.
Related Publications
Interested in Collaborating?
We welcome partnerships with institutions, NGOs, and researchers working at the frontier of AI and this domain.