I am a recent Ph.D. graduate in Computing from the SPIKE Research Group at Imperial College London, where I was advised by Alessandra Russo, Krysia Broda, Mark Law and Anders Jonsson. My research focused on the learning and exploitation of (hierarchies of) finite-state machines in reinforcement learning, using them as a means for task decomposition and temporal abstraction.
During my Ph.D. studies I interned at InstaDeep, where I worked on solving combinatorial optimization problems using reinforcement learning. Before starting my Ph.D., I was a research assistant in the Artificial Intelligence and Machine Learning Group at Universitat Pompeu Fabra, where I worked on enabling action concurrency in multiagent planning and temporal planning.
- ICMLHierarchies of Reward MachinesInternational Conference on Machine Learning (ICML), 2023
- NeurIPSWinner Takes It All: Training Performant RL Populations for Combinatorial OptimizationNeural Information Processing Systems (NeurIPS), 2023
- JAIRInduction and Exploitation of Subgoal Automata for Reinforcement LearningJournal of Artificial Intelligence Research (JAIR), 2021
- AAAISolving Multiagent Planning Problems with Concurrent Conditional EffectsAAAI Conference on Artificial Intelligence (AAAI), 2019