Amedeo Ranaldi
Ph.D. fellow in Computer Science and Artificial Intelligence, Sapienza University of Rome
Amedeo Ranaldi received the B.Sc. in Computer Engineering and the M.Sc. (cum laude) in Data Science from Sapienza University of Rome, Rome, Italy, in 2018 and 2021, respectively. He is currently a Ph.D. fellow in Computer Science and Artificial Intelligence and a member of the Prometheus Lab at the Department of Computer Science, Sapienza University of Rome. Within the lab, he is a key contributor to research projects on Wi-Fi-based computer vision and autonomous artificial intelligence systems deployed on UAVs. His research interests span Signal Processing, Computer Vision, Wi-Fi Sensing, EEG Signal Analysis, Human–Computer Interaction, Deep Learning, Machine Learning, Representation Learning, Time-Series Analysis, Affective Computing, Action and Gesture Recognition, Anomaly Detection, Embedded AI, and Real-Time Systems for Perception and Control. He is also experienced in data engineering and software development, with strong programming skills in Python, Java, and SQL, and practical knowledge of major libraries and tools such as TensorFlow, PyTorch, OpenCV, and Apache Spark.
Workshop
Computer Vision Techniques for Autonomous Driving in Simulated Environments
This course provides a practical introduction to deep learning techniques for autonomous driving, with a focus on utilizing simulated environments. In particular, it leverages Grand Theft Auto V as a data-rich platform for experimentation. Students will learn how to design a computer vision pipeline by starting from dataset preprocessing and augmentation, developing an end-to-end convolutional neural network (CNN) for steering angle prediction, and tackling real-world challenges such as object detection for braking systems using YOLOv5.
