Mission-critical defense analytics with computer vision and predictive modeling.
During my tenure at Quest Defense, I led the development of three mission-critical analytics projects for defense applications. The most significant was a predictive parts inventory system using Random Forest with isotonic regression calibration, reducing equipment downtime by optimizing spare parts availability. Another major initiative involved training a custom YOLO object detection model on synthetic imagery generated with Unreal Engine, enabling real-time analysis of drone reconnaissance footage. These projects operated under strict security requirements and earned me Employee of the Quarter recognition for exceptional performance in a high-stakes environment.