Pietro Lio

Name:	Pietro Lio
Affiliation:	The Computer Laboratory, University of Cambridge
E-mail:	(only provided to users who are logged into talks.cam)
Last login:	4 Apr 2026, 4:23 p.m.

Public lists managed by Pietro Lio

• Artificial Intelligence Research Group Talks (Computer Laboratory)

Talks given by Pietro Lio

Obviously this only lists talks that are listed through talks.cam. Furthermore, this facility only works if the speaker's e-mail was specified in a talk. Most talks have not done this.

• Modelling Epidemics

Talks organised by Pietro Lio

This list is based on what was entered into the 'organiser' field in a talk. It may not mean that Pietro Lio actually organised the talk, they may have been responsible only for entering the talk into the talks.cam system.

• Ensemble inequivalence for systems with long-range interactions
• Protein Misfolding in rare diseases: Hereditary Transthyretin Amyloidosis
• Large Language Models and Graph Neural Networks for Intelligent Manufacturing Systems
• GNN-ACLP: Graph Neural Networks Based Analog Circuit Link Prediction
• Hierarchical Protein Structure Representation Learning via Topological Deep Learning
• Google DeepMind’s Gemini models and the Rise of Long-Context LLMs
• From Score to Sound: Music Generation in the AI Era
• Computer Vision: Between Forensics and Biomedical Imaging
• On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning
• Incorporating Flexibility in Antibody-Antigen Interaction Prediction
• Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks
• Network modelling and Graph Neural Networks for emergency healthcare management
• Harnessing Large Language Models for Medical Data Processing: Structured Information Extraction, Disease Classification, and RAG Integration 
• From Machine Learning to Machine Reasoning -- Why Machine Learning Cannot Reach the Rigour of Logical Reasoning? recorded: https://www.youtube.com/watch?v=x38GySbuGJg
• Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers
• Expanding the borders of Multimodal Graph Learning with Sheaf Neural Networks
• Sheaves for Heterogeneous Data
• Enhancing Climate Prediction with Knowledge-Infused Deep Learning Models
• Personalising Crutch Geometries through Bayesian Optimisation
• Multi-Agent Graph Learning-Based Optimization and its Applications to Computer Networks
• Spectral Graph Neural Network: Polynomial Approximation and Optimization
• Scattering Networks and Singular Values Decomposition: different methods to remove background in Single-Molecule Localization Microscopy image
• Sphere Neural-Network for Higher-level Cognition
• Protein generation and fitness optimization
• MaRF: Representing Mars as Neural Radiance Fields
• Unveiling Bounded Confidence Dynamics in Sheaf Neural Networks
• Improving learning with noisy labels in two possibile scenarios.
• Integrating Radiomics and Explainable Methods: Paving the Way for Transparent and Interpretable Medical Imaging Analysis
• Relative representations enable zero-shot latent space communication
• Learning Multi-Scene Absolute Pose Regression with Transformers
• ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
• The Problem of Size Generalization in Graph Neural Networks
• Neighbourhood matching creates realistic surrogate temporal networks
• On the Two-fold Role of Logic Constraints in Deep Learning
• Understanding the loss landscapes of large neural networks: scaling, generalization, and robustness
• The Age of Predictive Medicine
• A Standard-Enabled Workflow for Synthetic Biology
• Adversarial generation of gene expression data
• Metabolically driven latent space learning for gene expression data. A journey through manifolds and Pareto fronts
• High-Performance Computing Applied to Computational Intelligence in Systems Biology and Genome Analysis
• Computer-Assisted Analysis of Biomedical Images
• Exploiting spatial features in the analysis of ChIP- and BS-Seq data
• Stochastic hybrid systems: modelling cancer and psoriasis
• Delta-complete decision procedures and hands-on tutorial
• Nonlinear real arithmetic and delta-satisfiability
• Bayesian factorization of multiple data sources