معرفی
Giulio Rossolini is an Assistant Professor (from June 2024) specializing in adversarial machine learning, computer vision, and deep learning security. Previously, he was a Postdoctoral researcher (Jan 2024) and a PhD student (Oct 2020–Mar 2024). His work focuses on enhancing the robustness of AI systems against adversarial attacks, particularly in autonomous driving and vision applications.
Key research areas include adversarial defense mechanisms, dataset generation for robustness evaluation, and safety-critical AI systems. He has contributed to frameworks like CARLA-GeAR and TrainSim for systematic evaluation of deep learning models. Notable achievements include the IEEE TCCPS Early-Career Award 2023.
His publications span topics such as real-time adversarial defenses, synthetic dataset development, and ethical AI considerations. Current projects emphasize bridging gaps between theoretical robustness and practical deployment in autonomous systems.
