I am a computer scientist working as postdoctoral research fellow at University College London together with Mirco Musolesi. I create and study artificial intelligence techniques for networked systems, with a particular interest in developing algorithms for challenging decision-making problems that arise in the real world.


[Apr 2023] Thrilled to have passed my PhD viva with no corrections for my dissertation "Learning to Optimise Networked Systems". I am grateful to my examiners Pietro Liò (University of Cambridge) and Simon Julier (UCL) for the stimulating conversation.

[Feb 2023] Our work Graph Reinforcement Learning for Operator Selection in the ALNS Metaheuristic was accepted for presentation at the International Conference in Optimization and Learning (OLA2023). We propose a hybrid method that combines RL and the ALNS metaheuristic, improving significantly on the operator selection mechanism in this classic method.

[Jan 2023] New work out in Proceedings of the Royal Society A: Planning spatial networks with Monte Carlo tree search. We propose a tree search framework for the construction of spatial networks. We improve in scalability over prior reinforcement learning methods, and perform case studies for improving the resilience and efficiency of Internet networks and metro systems.

[Jan 2023] Our paper RLQ: Workload Allocation With Reinforcement Learning in Distributed Queues has been published in IEEE Transactions on Parallel and Distributed Systems. We propose a scheduler for distributed task queues based on reinforcement learning. An implementation for the Celery framework in Python is available.