BUILD DISTRICT
A pixel city where each building is a major project.
Responsible AI Hospital
An AI-assisted clinical triage system that prioritises colonoscopy referrals by patient risk while maintaining fairness, transparency, and clinical accountability.
An AI-assisted clinical triage system developed to prioritise colonoscopy referrals based on patient risk factors while maintaining fairness, transparency, and clinical accountability. The system predicts urgency categories and supports healthcare professionals by identifying high-risk patients earlier while providing explainability metrics and fairness auditing across demographic groups. The project was developed with a strong focus on responsible AI principles and healthcare decision support.
Clinical Operations Centre
A full-stack clinical decision support platform that augments clinicians with contextual AI suggestions, structured patient summaries, and audit-ready decision trails.
A full-stack clinical decision support platform designed to assist healthcare professionals by generating contextual AI recommendations, structured patient summaries, and audit-ready decision trails. The system demonstrates how AI can augment clinical workflows while preserving human oversight, transparency, and accountability. Special attention was given to security, explainability, and role-based access controls.
Developer Tools Tower
A privacy-first AI diagramming platform where all processing occurs locally on the user's device, generating architecture diagrams from structured inputs entirely offline.
A privacy-first AI-powered diagramming platform where all processing occurs locally on the user's device. The application generates software architecture diagrams from structured inputs while ensuring complete data ownership and offline functionality. The project explores local-first software architecture, AI-assisted development tools, and privacy-preserving design principles.
Data Science Laboratory
A machine learning regression system that predicts insurance premiums from demographic and health-related factors with calibrated confidence estimates.
A machine learning regression system developed to predict insurance premiums using demographic and health-related factors. Multiple regression models were evaluated and compared to improve predictive performance and generate calibrated confidence estimates. The project focused on feature engineering, model selection, and interpretability.
Security Operations Facility
A cybersecurity investigation project analysing live network traffic, identifying anomalies, detecting attack patterns, and documenting defensive response procedures.
A cybersecurity investigation project focused on analysing live network traffic, identifying anomalies, detecting attack patterns, and documenting defensive response procedures. Using industry-standard security tools, the project explored network monitoring, packet analysis, threat detection, and incident response workflows.
