Projects Highlights & Completed Systems
1. Embrace Study (NDA)
August 2026
Description
Built secure participant-tracking infrastructure for a 200+ person prospective study on maternal-infant postpartum psychological adjustment. Architected the entire platform using Next.js, ShadCN, and Supabase, ensuring robust role-based access control, interpretable longitudinal insights, and strict medical-grade data protection.
(Source code and live deployment restricted under non-disclosure agreement).
2. Diabetic Retinopathy Screening (Champion @ NAIC 2026)
June 2026
Description
Developed a computer vision diagnostic pipeline for clinical retinal image analysis to detect diabetic retinopathy.
- Preprocessing Pipeline: Implemented Contrast Limited Adaptive Histogram Equalization (CLAHE), Graham’s Method for local color normalization, and Feature Adaptive Cropping to isolate retinal regions and eliminate lighting variations using OpenCV and NumPy.
- Model Architecture: Trained an ensemble architecture combining ResNet-34, EfficientNetB4, and a Random Forest meta-classifier, reaching 91% accuracy on limited, highly unbalanced clinical datasets.
Source code: Diabetic Retinopathy Screening GitHub
3. Byte of Kuih (1st Runner Up @ NAIC 2025)
July 2025
Description
Curated, augmented, and cleaned a proprietary dataset of over 16,000 images representing 8 traditional Malaysian kuih classes under diverse lighting, orientations, and backgrounds. Fine-tuned an EfficientNetV2 model using PyTorch and Hugging Face Transformers, reaching 98% validation accuracy and 100% test accuracy.
Read the full breakdown: National AI Competition 2025 Post
Model repository: NAIC Model 2025 GitHub
4. JotMe (Best Beginner Project @ LingHacks VI)
June 2025
Description
A mental-health digital journaling web application powered by NLP. Integrates KeyBERT for keyword extraction with fine-tuned emotion-detection transformer models, combined with a NetworkX graph-based contextual sentiment analysis algorithm to detect sarcasm and nuanced expressions, generating real-time crisis-intervention alerts and interactive ChartJS mood trends.
Read the hackathon story: LingHacks VI Blog Post
Source code: JotMe GitHub
5. Generative User Interface for Differential Evaluation via Symptom Analysis and Record Keeping (GUIDE-SHARK)
March 2025
Description
Designed to relieve hospital and emergency room overcrowding by giving patients a preliminary symptom screening before triage. Features a clean cross-platform Flutter frontend, coupled with a Django REST backend and PyTorch machine learning models to analyze multi-modal patient symptoms and suggest preliminary differential diagnoses.
Frontend Repository: GUIDE-SHARK Frontend
Video Showcase:
Additional / Earlier Projects
- Artificial Intelligence with Reprompting & Code Execution: Iterative code generation and evaluation inspired by AlphaEvolve. GitHub
- Maker Kehadiran: Custom MVC web application in PHP & MySQL for attendance tracking. GitHub
- Study Scroll: Educational revision tool leveraging doom-scrolling micro-habits for A Level students. GitHub
