Developed a system to detect suspicious web interactions using ML and Deep Learning models. Processed web traffic datasets with feature engineering and created visualizations for real-time anomaly detection.

Developed a full-stack FinTech platform using React, Node.js, Express, and MongoDB to detect and prevent fraudulent loan applications through secure authentication and real-time data monitoring. • Built an interactive Admin Dashboard (Vite + shadcn UI) with JWT-based login, API integration, and analytics visualization for fraud trend analysis and risk assessment.

Built a predictive maintenance system for industrial motors, achieving 93.13% accuracy in diagnosing critical faults. This solution can minimize downtime in critical infrastructure , enhancing operational efficiency and reducing maintenance costs. • Simulated 6 critical fault conditions across 3 torque levels, generating 40K+ labeled data points via MATLAB/Simulink.Built scalable ML pipeline with 10+ engineered features, optimized using grid search and 5-fold cross-validation..