AI system development for PhishGuard and Cheating Surveillance-style real-time detection projects
Built and integrated AI/ML systems for real-time detection and analytics in security and product features. The work involved developing computer-vision and machine-learning pipelines that produce model outputs such as classifications, risk scores, and tracked detections for downstream decisions. It also included preparing application logic and model interfaces for interactive use in a web context. • Implemented computer vision components using OpenCV/dlib/YOLOv5-style workflows in an examination-surveillance system concept. • Engineered a phishing detection system using Logistic Regression and Random Forest with live URL analysis and risk scoring. • Designed real-time dashboards and predictive analytics endpoints for monitoring and decision support. • Developed full-stack interfaces to run AI inference and present classification results to users.