BurnOut Radar is a Full Stack Web Application build using React.js & Supabase for developers to track mental state, coding habits, and burnout risk. Features daily logs, dashboards, interactive charts, profile settings, and light/dark mode.

ML-powered Decision Support System for burnout risk prediction and personalized productivity analysis. Interactive Jupyter dashboard with gap analysis and actionable recommendations.

🏢 Remote Work Burnout Prediction using Explainable AI (XAI). Features advanced behavioral engineering, XGBoost/LightGBM comparisons, and a focus on Recall for high-risk employee detection. Includes a strategic Senior Audit Report. 🚀

This project focuses on predicting employee burnout using machine learning techniques. Various models such as Logistic Regression, Decision Tree, Random Forest, and XGBoost were implemented and compared.

MVP para previsão de risco de Burnout

Burnout Checkup is an interactive dashboard designed to explore the relationship between AI tool usage, workload characteristics, and employee burnout risk.

Interactive Dashboard for Workplace Burnout Analys

A sustainable productivity analytics system that tracks tasks, focus sessions, and daily reflections to measure long-term productivity and detect burnout risk.

Analyzing and predicting employee burnout using various employee features.