My Projects

Interned as a solo developer to design and launch a modern, responsive business website for a B2B poultry supplier in Myanmar. Features include an interactive home page, dynamic product listing, and a contact us form linked to the company's email. Currently working on a machine learning project to detect chicken that are not laying eggs in the farm.

3rd runner-up (Top 4 out of 400+ teams), best team for Problem Statement 3: Redefining Level 2 Product Ops. Developed an AI diagnostic assistant for PSA duty officers to automates alert parsing, root cause analysis, and resolution planning with integrated ticketing and analysis system.

AI wellness companion for seniors featuring real-time voice chat, a hobby hub with 30+ activities, and the SeniorGram social feed. Accessibility-first design with multilingual support, high contrast UI, and HeyGen streaming avatars powering natural conversations and community class bookings across Singapore.

SentinelAI set out to build an AI-powered safety system using CCTV/IP cameras to detect falls, strokes, and industrial accidents in real time. It was submitted to the NUS SoC VIP 10k grant and IDEATE ...

Finalist (Top 10 out of 60+ teams), best usage of data, best team for Theme 1: Health and Wellbeing. React Native app that integrates real-time Singapore health data, GPT-powered guidance, and community reporting to build an AI-driven, multilingual public health ecosystem.

Finalist (top 20 of 80+ teams). React Native app that uses AI and community insights to detect online scams, analyze suspicious URLs, and educate users through interactive modules, analytics, and a scam discussion forum.

Designed and implemented a modular event-driven simulator in Java, using functional programming concepts and stream pipelines to model a multi-server queuing system. The project emphasized effect-free design and immutability.

Modern Next.js web app that helps users track their recovery journey, earn achievements, and stay motivated with streaks, rewards, and community support.

Top 3 (Called for top 3 in University Category out of 93 teams, final ranking undetermined due to absence from oral presentation). Developed an end-to-end NLP pipeline leveraging DistilBERT to classify vessel deficiency severity from PSC inspection reports, including data cleaning, label resolution, and model fine-tuning.