About
Hi, I’m Federico 👋. I am an AI Researcher at Intesa Sanpaolo in Turin. I received my Ph.D. in Data Science from Sapienza University of Rome.
My research focuses on AI and optimization for information ecosystems, studying how intelligent systems learn from and interact with external information sources such as web content, social media, and institutional communication.
I currently work on:
- LLM safety — overrefusal and hallucinations
- AI agents with web access — auditing bias in retrieved sources
- Online learning — low-rank matrix bandits
- Financial markets — predicting ESTR swaps and SOFR from ECB, Fed, and macroeconomic releases
My work combines machine learning, graph mining, reinforcement learning, and mathematical optimization.
Feel free to reach out if you’re interested in collaborating ✉️ federico dot cinus [at] intesasanpaolo dot com
Latest News
March 2026
- 📄 New Preprint: A Survey on Algorithmic Interventions in Opinion Dynamics. Read it here.
February 2026
- 🛡️ Co-founded dotNex: Developing AI systems to detect and analyze information operations on social media.
January 2026
- 🎉 Paper accepted at ICLR 2026: Online Minimization of Polarization and Disagreement via Low-Rank Matrix Bandits .
November 2025
- 📄 New preprint (Under review): Auditing LLM Editorial Bias in News Media Exposure .
October 2025
- 📊 🔍 Released an interactive tool to explore inferred sociodemographic patterns across subreddits: reddit-fabric.
- 📄 New preprint (Under review): Online Minimization of Polarization and Disagreement via Low-Rank Matrix Bandits .
August 2025
- 🎤 Honored to present our paper at the International Joint Conference on Artificial Intelligence (IJCAI 2025) in Montreal 🇨🇦.
July 2025
- 🎉 Paper accepted at EPJ Data Science: Measuring how computer science research translates into innovation and development.
May 2025
- 🎓 Earned my Ph.D. in Data Science (cum laude) from Sapienza University of Rome.
- 🎉 Paper accepted at KDD 2025: Engagement-Driven Content Generation with LLMs.
April 2025
- 🎉 Paper accepted at IJCAI 2025: Minimizing Polarization and Disagreement in the Friedkin-Johnsen Model with Unknown Innate Opinions. See you in Montreal!
- 🎓 Presented at WWW 2025 in Sydney.
March 2025
- 🎉 New paper accepted at TIST.
- 🎓 Completed reviews for KDD 2025.
February 2025
- 📄 New Preprint: Minimizing Polarization and Disagreement in the Friedkin-Johnsen Model with Unknown Innate Opinions. Read it here.
- 📄 New Preprint: On the Inference of Sociodemographics on Reddit. Check it out here.
January 2025
- 🎉 Accepted at The Web Conf 2025! Our paper Exposing Cross-Platform Coordinated Inauthentic Activity in the Run-Up to the 2024 U.S. Election has been accepted! Read the preprint here.
December 2024
- 🎓 I'm happy to be reviewing papers for The Web Conference 2025.
- 📄 New Preprint: We've just published a preprint exploring how large language models can generate content optimized for user engagement using "social" reinforcement learning and opinion dynamics. Check it out here.