Actively pursuing independent research and projects focused on developing and deploying open-source AI/ML solutions for infrastructure analytics, ensuring the continuous application of expertise and technical leadership.

Led research utilizing AI/ML, UAV-based platforms, and human-centric data (Eye Tracking) to develop and deploy reliable, intelligence-driven systems for faster and more accurate infrastructure inspection.

Developed and deployed Deep CNN and Computer Vision systems for site automation. Core deliverables included a UAV-based platform for high-accuracy asset diagnostics and a real-time monitoring system for construction safety and risk compliance.

Designed and prototyped a complete end-to-end IoT solution for power transmission lines, integrating custom non-contact hardware with a cloud-based dashboard for real-time fault identification and data analysis.

Thesis: From Gaze to Insight: Leveraging Eye Tracking for Structural Inspection

Thesis: Bridge Inspection Using an Unmanned Aerial Vehicle by Image Capturing and Geo-tagging System and Deep Convolutional Neural Network

Thesis: FPGA-based Digital Signal Processing of Under-sea Range Finder