AI: Facial Emotion Recognition using VGG16 with transfer learning.

Data Science: Customer segmentation using K-means with Elbow Method and silhouette analysis.

Distributed Systems: Containerised microservices using Docker and infrastructure-as-code on Azure.

• Defined functional requirements, set milestones, and ran Agile sprints to take a conversational AI platform from design through to production on the App Store and Play Store, supporting 50,000+ users.

• Architected an AI and RAG pipeline with NLP-driven retrieval, reducing response time by 80% through document re-chunking, pre-computed embeddings, reranking, and WebSocket streaming.

• Deployed containerised cloud infrastructure on AWS and Hetzner using Docker, managing CI/CD and production monitoring.

• Coordinated between designers, developers, and external stakeholders, translating technical decisions into clear priorities across mobile, web, and cloud workstreams.

• Collaborated on system design and feature delivery for a production platform handling sensitive data, contributing to security and data-handling decisions from the start.

• Built front-end interfaces for mobile and web using React, React Native, and TypeScript.

• Contributed to back-end services using Django, FastAPI, and ExpressJS with PostgreSQL and MongoDB.

• Built and published a cross-platform React Native date/time picker as a TypeScript-based, open-source NPM package with rich modes, themable UI, and locale handling.

• Built an AI-powered learning system that converts PDFs into flashcards, study guides, and structured notes using Google Gemini AI within a Next.js + TypeScript architecture.

• Covered 300+ lecture slides (an entire academic year) in 2 days, resulting in First-Class grades.

• Built an AI-powered adaptive learning mobile app in Flutter for neurodiverse learners, integrating Azure OpenAI for dynamic content adaptation and SQLite for local storage.