Integrating Graph Representation Learning and Diffusion: Computational Models and Applications in Chemistry and Medicine.
Speaker:
Pietro Liò
Data dell'evento:
Tuesday, 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.
gruppo di ricerca: