Lucky Ajidoku

Developed an ArcFace-powered facial recognition module, enhancing identity verification accuracy by matching user selfies against NIN/BVN-linked government ID images.

Engineered and deployed a real-time liveness detection system utilizing challenge-response techniques (e.g., blink, head-turn), effectively preventing biometric spoofing and bolstering system security.

Designed and integrated a Python AI microservice for scalable face embedding generation and liveness verification within a multi-service architecture, improving system efficiency.

Seamlessly integrated critical biometric features into the YoTouch verification pipeline and backend scoring engine (Node.js/PostgreSQL), optimizing data flow and processing speed.

Ensured stringent NDPR and GDPR compliance by architecting an off-chain biometric data storage solution on a Cardano blockchain, safeguarding sensitive user information.

Monitored critical immunization exercises across Nasarawa State, collecting high-quality structured data using ODK digital questionnaires to ensure program efficacy.

Analyzed comprehensive field data to derive actionable insights, which were presented at ward-level review meetings, directly informing and supporting health decision-making processes.

Led the development of EnergizeAI, an AI-powered solar PV system blueprint designer, earning national recognition as the "Best Project" at the 3MTT June Knowledge Showcase 2025.

Architected and deployed diverse ML models across NLP, computer vision, recommendation systems, and predictive analytics, demonstrating versatility in AI application.

Executed end-to-end data preprocessing, feature engineering, model training, and rigorous evaluation using Python and Jupyter, ensuring robust model performance.

Effectively communicated complex technical project outcomes to facilitators, receiving commendation for clarity and impact, enhancing stakeholder understanding.