A few of my favourite builds — from early-warning systems for rockfall to full-stack ML monitoring dashboards.
A modern productivity platform that helps students organize their academic workflow through task management, notes, scheduling, and performance tracking — combining an intuitive interface with productivity-focused tools in one centralized workspace for planning and monitoring study progress.
Includes a rich-text Notes module with folders and formatting, an interactive Calendar, an analytics dashboard for productivity score and study streaks, a built-in Pomodoro timer, and secure login/signup — wrapped in a responsive, glassmorphism-inspired UI.
An AI-powered early warning system that flags rock instability from micro-vibration and acoustic signals, catching pre-failure patterns before visible cracks appear. Built a zone-based digital mine model with real-time heatmap visualization, plus Explainable AI and SMS alerts for proactive risk mitigation.
A full-stack ML drift monitoring platform using PSI, chi-square, T-test, and F-test methods to detect dataset drift — with interactive explainability dashboards, control chart monitoring, and risk scoring via FastAPI and Chart.js. Deployed on GitHub Pages and Render, validated on real-world datasets including the UCI Air Quality dataset.
A hardware-based expense tracking system built with ESP32, RFID, a keypad, and an OLED display for automated logging and user identification — with offline storage, optional cloud sync, split-bill calculation, and real-time feedback display.