Integrating Graph Representation Learning and Diffusion: Computational Models and Applications in Chemistry and Medicine.
Speaker:
Pietro Liò
Data dell'evento:
Martedì, 11 July, 2023 - 11:30
Luogo:
Aula Magna
Contatto:
fsilvestri@diag.uniroma1.it
Title: Integrating Graph Representation Learning and Diffusion: Computational Models and Applications in Chemistry and Medicine.
Abstract
The talk will focus on recent methodological novelties and challenges in graph representation learning (fundamentals, higher-order networks, and higher-order message passing networks). Then, I will describe why diffusion is an interesting new research direction.
I will provide various examples of graph representation in science and medicine.
I will conclude with some technical and ethical considerations on the actionability and deployment of AI in medical practice.
Short Bio
Pietro Lio' is a Full Professor in the Department of Computer Science and Technology at the University of Cambridge, where he is also a member of the Artificial Intelligence group. His research is primarily centered on the development of Artificial Intelligence models applied to many sectors of science and Mathematics such as: physics, biology, chemistry, and medicine. His current focus is on Graph Neural Network modeling.
Prof. Lio' boasts an impressive academic background, holding a Master of Arts degree from Cambridge, along with two PhDs. One is in Complex Systems and Non-Linear Dynamics, earned from the School of Informatics, Department of Engineering at the University of Firenze, Italy. The other is in Theoretical Genetics, awarded by the University of Pavia, Italy.
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