I am a Computer Scientist specializing in neuro-symbolic AI, multi-agent systems, and epistemology. Currently, I am investigating the Computational Foundations of AI, with a particular focus on Understanding Decision Making.
Hi, I’m Francesco Fabiano, a Computer Science Ph.D. passionate about AI. I’m from Parma, Italy, and of course, I love good food, especially when I can enjoy it with my lifelong friends.
Academia allowed to meet amazing people and work with incredible research groups. Together, we’ve explored everything from epistemic planning to hybrid AI architectures inspired by human cognition.
I love spending my time figuring out creative ways to represent and manipulate information using logic. It’s like solving puzzles all day!
Recently I’ve been focusing on automated planning and neuro-symbolic systems that combine the power of logic with the adaptability of machine learning.
I do a lot of running, and I especially enjoy trail-running in the hills of Calestano—my favorite place on Earth. While I’m definitely an amateur, the breathtaking views make every step worth it!
I am fascinated by mythology, especially how myths and legends shape the diverse cultures around the world. Here some of my favorite sources: the Mythology Podcast, Kojiki, and Ted-ED playlist.
Part of an IBM Watson Research Lab Group, led by Dr. Rossi, comprised of researchers from IBM and various universities. With this research group, we are analyzing well-known cognitive theories to define a general AI paradigm starting from cognitive theories such as the one popularized by D. Kahneman in his book Thinking Fast and Slow.
Structured and taught undergraduate and graduate courses at the Computer Science Department. Furthermore, I focused on research in neuro-symbolic AI, automated planning, multi-agent epistemic reasoning, and computational logic.
Courses
Structured and taught the undergraduate and graduate courses offered by the Decision & System Sciences curriculum at the Erivan K. Haub School of Business. Moreover, I focused on research in applied AI, neuro-symbolic AI, automated planning and computational logic.
Courses
Structured and taught the undergraduate course Typing in LaTeX, open to all the students of the University. The course was designed to help the students acquire the necessary capabilities to realize documents using the typesetting language LaTeX. The teaching was comprised of 24 hours (equivalent to 3 Italian credits) of frontal lectures and exercises. Finally, the evaluation was based on a project.
Courses
Research Title: Artificial Intelligence for packaging production line.
Implemented an automated reasoning tool that makes use of innovative techniques (e.g., constraint programming, planning, etc.) to model production processes and that returns an optimized and safe plan that controls the robotic components in the production line.
Migrated the website of the College of Arts and Sciences to a user-friendly platform to simplify the College’s staff work. After the migration, support and maintenance for the website was provided.
Studied, under Prof. Enrico Pontelli, the design of an epistemic forward planner with particular attention to heuristics for the solving process and optimizations for the underlying knowledge representation.
The SOFAI project project whose aim is to advance AI by leveraging cognitive theories of how humans make decisions, with particular focus on the Thinking Fast and Slow theory of Daniel Kahneman. The project is led by IBM Research in collaboration with several academic partners.
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This project implemets a solver, called EFP, designed following the imperative programming paradigm. In particular, the solver is fully developed in C++. EFP is a general and comprehensive epistemic forward solver that can solve problems defined in mA*. Moreover, thanks to the introduction of agents’ attitudes and other capabilities, the planner allows the users to tailor actions in whichever fashion they prefer without having to worry about tedious and intricate effects definitions.
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The SDG Dashboard is a collaborative data reporting and analytics platform for global business schools to share their best practice impacts on the United Nations Sustainable Development Goals (SDGs) and transform business education into a force for good.
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SYNERGY (Symbolic and Neuro-Symbolic Architectures for Intelligent Robotics Technology) is a workshop that aims at fostering in-depth discussions on Knowledge Representation (KR) and neuro-symbolic architectures with the goal of advancing intelligent robotics to new levels of sophistication. SYNERGY 2024 was held at the 21st International Conference on Principles of Knowledge Representation and Reasoning (KR 2024).
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The ICLP & LPNMR Doctoral Consortium (ICLP/LPNMR-DC 2024) and the Autumn School on Logic Programming have taken place during the 40th International Conference on Logic Programming (ICLP 2024) and the 17th International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR 2024) in Dallas, Texas, US, on October 12-13, 2024.
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The 19th Doctoral Consortium (DC) on Logic Programming was part of the 39th International Conference on Logic Programming (ICLP 2023). The DC provided students and early career researchers with the opportunity to present and discuss their research directions, obtain feedback from both peers and experts in the field, and participate in mentoring sessions on how to prepare for a research career. In particular, the DC hosted leaders in logic programming research, from academia and industry, that gave talks on their research areas and comment on the presented works, providing valuable insights for early career researchers.
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The following document contains supplementary information for the paper H-EFP: Bridging Efficiency in Multi-Agent Epistemic Planning with Heuristics submitted to The 25th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2024).
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The following document contains my Ph.D. Thesis titled Planning while Believing to Know.
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The following document contains my Master of Science Thesis titled EFP and PG-EFP: Epistemic Forward Planners in Multi-Agent Domains.
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The following document contains my Master of Science Thesis titled Load Distribution Analysis in an MPI Framework. Unfortunately, this thesis is only available in Italian, sorry!
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The following document contains my Curriculum Vitae.
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