SAMELE STEFANO
Research assistant
Research collaborator
Research collaborator
Stefano Samele is a postdoctoral researcher at the Artificial Intelligence and Robotics Lab (AIRLab), part of the Department of Electronics, Information, and Bioengineering of Politecnico di Milano.
He earned a Master’s degree in Mathematics from the University of Milan, graduating summa cum laude, before getting a second-level Master’s degree in Artificial Intelligence from the University of Turin also with highest honors. He joined Politecnico di Milano for an industrial Ph.D. in Computer Science and Engineering supervised by Prof. Matteo Matteucci and in collaboration with Pirelli, successfully defending my thesis in April 2025.
His research centers on anomaly detection in industrial product images, where he has addressed highly complex scenarios characterized by big composite objects, subtle defects and varying production conditions. His interests also include adversarial attacks and defenses, neural architecture search, and zero/few-shot segmentation methods. He served as a teaching assistant for courses in Machine Learning and Computer Science, and co-supervised several thesis in the field of Deep Learning.
He earned a Master’s degree in Mathematics from the University of Milan, graduating summa cum laude, before getting a second-level Master’s degree in Artificial Intelligence from the University of Turin also with highest honors. He joined Politecnico di Milano for an industrial Ph.D. in Computer Science and Engineering supervised by Prof. Matteo Matteucci and in collaboration with Pirelli, successfully defending my thesis in April 2025.
His research centers on anomaly detection in industrial product images, where he has addressed highly complex scenarios characterized by big composite objects, subtle defects and varying production conditions. His interests also include adversarial attacks and defenses, neural architecture search, and zero/few-shot segmentation methods. He served as a teaching assistant for courses in Machine Learning and Computer Science, and co-supervised several thesis in the field of Deep Learning.
