Andrea
Asperti


Asperti
Italy Full Professor of Machine Learning and Deep Learning University of Bologna Extended Faculty
Email contact

Andrea Asperti is full professor of Machine Learning and Deep Learning at the University of Bologna. He currently represents the University of Bologna for the area of Data Science and Artificial Intelligence within the UnaEuropa Alliance. He earned a Ph.D. in Computer Science from the University of Pisa in 1989. Throughout his career, he has held various positions, including working at the Ecole Normale Supérieure in Paris and at INRIA-Rocquencourt. From 2005 to 2007, he held the position of Director of the Department of Computer Science at the University of Bologna. From 2000 to 2007, he was a member of the Advisory Committee of the World Wide Web Consortium (W3C). He is authors of hundreds of publications in international peer reviewed journals and conferences; and a few books. Over time, he has coordinated several National and European projects. He is fascinated by all aspects related to machine intelligence. Currently, he is mostly working on Deep Learning, Generative AI, Diffusion Models. He is also interested in Deep Reinforcement Learning.

COURSES

Neural networks are a class of machine learning algorithms, originally inspired by the brain, structured in layers of interconnected artificial neurons.

The network can be trained on data to optimize its connections to a specific task.

Deep neural networks, that is networks with multiple internal (so called hidden) layers, have recently seen a lot of success at practical applications. They’re at the heart of production systems at companies like Google and Facebook for image classification, speech recognition, natural language processing, language understanding or robotics.

The course gives an overview of the foundational ideas and the recent advances in neural nets, explaining the potentialities of the topic for practical purposes. We shall cover supervised and unsupervised techniques, methods for visualizing and understanding the behavior on neural nets, as well as adversarial techniques to fool them. We shall also hints to recent applications in the field of reinforcement learning, and some amazing results in game simulation.

Data Science and Business Analytics
Artificial Intelligence and Innovation Management
Finance and Fintech