About Me 🙋‍♂️

I am an associate professor in Computer Science at the University of Udine studying computer vision and machine (deep) learning.

Previously, I was an assistant professor (under tenure), and also spent a year as a visiting research scientist at the Video Computing Group at the University of California Riverside, under the guidance of Amit K. Roy-Chowdhury. I did my postdoctoral studies with Gian Luca Foresti at the Department of Mathematics, Computer Science, and Physics at the University of Udine. I completed my Ph.D.(s) in Multimedia Communication with a major in Computer Vision with Christian Micheloni, and in Information Engineering with a major in hierarchical learning architectures under the supervision of Gian Luca Foresti.

News 🚀

Serving as AC @ CVPR2025
Serving as AC @ ECCV2024
Paper Accepted at the NTIRE Super Resolution (x4) Challenge (ranked among best performing methods) @ CVPR2024
Paper Accepted at WACV2024

Research Group 👨‍🔬

The goal of our Machine Learning and Perception group is to scientifically understand (and mimick) intelligence.

We are interested in human-like intelligence, and extensively investigating machine learning algorithms, mostly deep neural networks, for a wide range of applications to help equip the world with the necessary tools to bring about a positive integration of AI into society.

We aim to advance the field of computer vision and pattern recognition by developing innovative algorithms and models. We aim to enhance the capability of machines to perceive, understand, and interact with the world through vision-based systems. Our research emphasizes the development of efficient and adaptive learning methods, robust pattern recognition techniques, and their application to real-world challenges in areas such as autonomous systems, biomedical image analysis, and object detection. By leveraging deep learning and machine learning paradigms, we strive to create intelligent systems that can operate autonomously and make informed decisions in complex environments.

Most relevant works include:

Computer Vision and Image Processing: Developing algorithms for object detection, segmentation, and image recognition.
Machine Learning and AI: Enhancing machine learning techniques for better performance in various applications.
Pattern Recognition: Designing systems for accurate pattern recognition in complex datasets.
Robotics and Autonomous Systems: Integrating AI and vision systems in robotics for autonomous operation.
Biomedical Image Analysis: Applying image processing techniques to medical images for diagnosis and treatment planning.

Teaching 👨‍🏫

Multimedia Communication and Information Technology:
Smart IoT Devices (2023-2024)

Multimedia Science and Technology:
Introduction to Programming for Multimedia Data Analysis (2023-2024)
Mutlimedia Computer Science (2023-2024)

Recent Papers 📰

Coming soon