At the University of Agder, I developed machine learning and deep learning models for detecting DDoS and spoofing in Internet of Vehicles CAN networks, achieving 96%+ accuracy and a 0.94 F1-score on test datasets.
I also built end-to-end CAN bus traffic analysis pipelines, covering preprocessing, anomaly detection, feature extraction, and performance evaluation. I collaborated with researchers at the University of Agder on AI-driven cybersecurity solutions for connected and autonomous vehicles.
As a Computer Vision Engineer Intern at the Institute of Marine Research, I developed YOLO-based pipelines to detect fish and localize head-tail keypoints in low-visibility underwater environments. I annotated and validated underwater fish images using Roboflow and applied OpenCV preprocessing and augmentation.
