Francesco Fuggitti
Francesco Fuggitti is a Scientist at the Bank of Italy -- Eurosystem, where he works on Distributed Systems and AI for national and European projects.
In 2022 and in 2023, Francesco was a Research Scientist at the MIT-IBM Watson AI Lab in Cambridge, MA (USA), where he contributed to the IBM Research's watsonx Orchestrate and watsonx projects.
In September 2023, Francesco graduated with a double PhD in Artificial Intelligence from Sapienza University in Rome (Italy) and York University in Toronto (Canada) through an international joint agreement. His doctoral research, supervised by Prof. Giuseppe De Giacomo and Prof. Emeritus Yves Lespérance, focused on Artificial Intelligence, Formal Methods, and Business Process Management and Automation.
Francesco became a qualified Professional Engineer in Italy in November 2020. In 2018, he earned an MSc in Engineering in Computer Science from Sapienza University, under the supervision of Prof. Giuseppe De Giacomo. Prior to this, he graduated in Industrial Engineering from the University Campus Bio-Medico of Rome in 2016, where he was supervised by Prof. Luca Vollero.
Francesco Fuggitti's main research interests concern the development of intelligent autonomous systems by combining Artificial Intelligence techniques and Formal Methods mathematical tools. In particular, Francesco works on temporal and dynamic logics, automata theory, sequential decision-making, conversational intelligence, natural language understanding, process management and automation, and large language models.
2018 Excellence Program, Sapienza University (among top 5% of the academic year)
Membro di
Awards
Ultime pubblicazioni
| Temporally extended goal recognition in fully observable non-deterministic domain models on APPLIED INTELLIGENCE | 2024 |
| A tool for declarative Trace Alignment via automated planning on SOFTWARE IMPACTS | 2023 |
| FOND Planning for Pure-Past Linear Temporal Logic Goals on 26th European Conference on Artificial Intelligence | 2023 |
| NL2LTL – a Python Package for Converting Natural Language (NL) Instructions to Linear Temporal Logic (LTL) Formulas on Vol. 37 No. 13: AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations | 2023 |
| Planning for Temporally Extended Goals in Pure-Past Linear Temporal Logic on Vol. 33 No. 1: Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling | 2023 |
| Temporally Extended Goal Recognition in Fully Observable Non-Deterministic Domain Models on | 2023 |
| From Natural Language to Workflows: Towards Emergent Intelligence in Robotic Process Automation on Lecture Notes in Business Information Processing | 2022 |