A web application utilizing machine learning models (Random Forest and Logistic Regression) to analyze and predict student dropout risks. This project combines advanced ML techniques with an intuitive interface for educational institutions.
Collaborated on the technical development and UI/UX design of a responsive portfolio website. This project showcases modern web development practices including semantic HTML, Tailwind CSS, and smooth interactions.
A web-based educational cooking game built as a Multimedia Systems final project. Players learn five recipes through drag-and-drop cooking mechanics, timer-based challenges, video answer keys, and an animated character that reacts to their performance — all crafted with HTML, CSS, and JavaScript.
A deep learning project implementing Zero-Reference Deep Curve Estimation (Zero-DCE) to enhance low-light images and video without paired training data. Built with Keras and TensorFlow in Google Colab, the model learns pixel-wise curve adjustments to restore brightness and detail, accompanied by a research paper documenting the methodology and results.