I design and deploy intelligent systems — from AI receptionists to personalised nutrition platforms — focused on real users, not hype.
AI/ML engineering, full-stack development, and cloud infrastructure. Focused on building production-ready intelligent systems.
Hackathons, university, and side projects.
Upload a photo of your room and Roomie's AI agent autonomously finds matching furniture on Facebook Marketplace, compares prices, and messages sellers on your behalf.
View on GitHub →Co-built and load-tested the backend for a university exam scheduling system handling room allocation and invigilator assignments, deployed on AWS with auto-scaling (1–4 instances) achieving 99.9% uptime.
View on GitHub →Implemented and fine-tuned a Siamese network to classify the ISIC 2020 Kaggle Challenge dataset and achieved 80% accuracy despite a severe 98:2 class imbalance.
Developed a research paper graph generation backend using Flask and SQLAlchemy to help academics find complex relationships between papers through filters such as thematic similarity, citations, and co-authors.
Built a match outcome predictor for Valorant using a gradient boosting model (Python, XGBoost) achieving 82% accuracy.
View on GitHub →Where I've worked and what I've built.
Active member of UQCS, UQRL, and UQIS.
Demos and project walkthroughs.
Interested in working together? I'd love to hear from you.