Summary
I am a researcher affiliated with the Centre for Explainable AI at Imperial College. My research largely focuses on safe & explainable AI, with special emphasis on contrastive explanations and their robustness. My work is currently supported by an Imperial College Research Fellowship.
Before, I was research associate in the Verification of Autonomous Systems group at Imperial College. I obtained a PhD in Computer Science from RWTH Aachen University and UNIGE with a thesis on AI Planning.
You might want to check out my CV to get a better picture of what I’ve done professionally so far.
Publications
Conference
Leofante F, Potyka N, Promoting Counterfactual Robustness through Diversity, The Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI24)
Jiang J, Rago A, Leofante F, et al. , Recourse under model multiplicity via argumentative ensembling, The 23rd International Conference on Autonomous Agents and Multi-Agent Systems, ACM
Jiang J, Lan J, Leofante F, et al. , Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation, The 15th Asian Conference on Machine Learning
Leofante F, Lomuscio A, 2023, Robust explanations for human-neural multi-agent systems with formal verification, The 20th European Conference on Multi-Agent Systems (EUMAS 2023), Springer, Pages:244-262, ISSN:1611-3349
Kouvaros P, Leofante F, Edwards B, et al. , 2023, Verification of semantic key point detection for aircraft pose estimation, The 20th International Conference on Principles of Knowledge Representation and Reasoning (KR2023), IJCAI Organization, Pages:757-762, ISSN:2334-1033