XXXVII Edition

Giancarlo Fortino

Giancarlo Fortino is Full Professor of Computer Engineering at the Department of Informatics, Modeling, Electronics and Systems (DIMES) of the University of Calabria (Unical), Rende (CS), Italy....

PhD course: Modelling and mining multilayer networks

A multilayer network is a network (or graph) wherenodes can be organised into sets, called layers, and the same node can belong to one or more of the layers. This allows us to model a wide range...

PhD Course: Advanced Deep Learning

The topic of this course will be the presentation of two advanced Deep Learning models: Graph Neural Networks (GNNs) and Deep Reinforcement Learning (DRL). ...

PhD Course: Emerging networking paradigms for 5G/6G systems

Future telecommunication networks will definitely be the key enablers for emerging critical services such as autonomous driving, smart industry, AR/VR, and remote medicine, that require low late...

PhD Course: Design of Experiments: Fundamentals and Modern Challenges

In this short course the fundamental principles, constructions and main theoretical results of the statistical theory of experimental design will be formulated. Different application areas, rece...

PhD Course: Advanced Cyber Security

The course aims at discussing the main methodological aspects of cybersecurity and at giving an overview of research issues that have recently received huge attention.By taking the course, the s...

PhD Course: A Primer on Resilient Control Methodologies for Cyber-Physical Systems

Recent progress on high-speed networks, wireless communication technologies and the development of novel control strategies for embedded systems gave rise to a boost in the deployment of the cyb...

PhD Course: Digital technologies and artificial intelligence law

The course focuses on the main legal aspects of digital technologies and artificial intelligence. ...

PhD Course: Mathematical Optimization for Machine Learning

The course is aimed at providing basic Numerical Optimization tools to handle some classes of Machine Learning problems, particularly focusing on supervised classification. Optimality conditions...

PhD Course: Quantum Computing and its Application to Machine Learning

The course will introduce the basic elements of quantum information and quantum computation. Starting from the physical fundaments (principle of superposition, unitary evolution, principle of me...