CV

Postdoctoral Researcher

• Research on explainable and trustworthy AI, with a focus on large language model behavior and applications to scientific discovery.
• Work Package and Task Leader in the ERC Proof of Concept project ILLUME-4-Science.
• Contributor to technology transfer (TRL 3 to TRL 5) and industrial collaborations, including ongoing work with Accenture on evaluation metrics for large language model explanations.

Postdoctoral Researcher

• Research on dimensionality reduction, low-rank approximation, clustering, and linear-algebraic methods for machine learning.
• Industrial collaboration with Helen Oy and House of AI on forecasting district-heating consumption using real-world data.

Doctoral Researcher

• Research on efficient and trustworthy algorithms for data mining and machine learning, within the Academy of Finland project Model Management Systems — Machine Learning meets Database Systems (MLDB).
• Research visits to Aarhus University, Denmark (2022, invited by Prof. Panagiotis Karras) and KTH Royal Institute of Technology, Sweden (2023, invited by Prof. Aristides Gionis).

Research Intern and Master's Thesis Student

• Research on temporal network analysis, focusing on extracting dense substructures and understanding spreading dynamics.

D.Sc. (Tech.) in Computer Science

• Thesis: Efficient and Trustworthy Methods for Knowledge Discovery.
• Advisor: Prof. Aristides Gionis. Opponent: Prof. Angela Bonifati (Université de Lyon).

M.Sc. in Data Science

• 110/110 cum laude (average grade 30/30).
• Thesis: Applications of the Temporal Core Decomposition in the Analysis of Temporal Networks. Supervisors: Dr. Francesco Bonchi and Prof. Stefano Leonardi.

B.Sc. in Statistics — Double Degree

• University of Bologna: 110/110 cum laude (average grade 30/30). University of Glasgow: B.Sc. (Hons), First Class Honours.
• Thesis: Facial Ageing. Supervisors: Prof. Adrian Bowman and Prof. Angela Montanari.

ILLUME-4-Science — ERC Proof of Concept (Horizon Europe)

• Work Package Leader (WP1, Demonstrating Scientific Impact) and Task Leader (risk factor identification; conversational interface for exploring explanations).
• Explainable AI for scientific and biomedical applications, in collaboration with partners including the University of Pisa and the German Cancer Research Center.

XAI — Science and Technology for the Explanation of AI Decision Making (ERC Advanced Grant)

• Postdoctoral research on interpretability and explainability of machine learning models.

FAIR — Future Artificial Intelligence Research (PNRR), Spoke 1 "Human-Centered AI"

• Research on human-centered, trustworthy and explainable AI.
• Technology transfer: development and validation of ILLUME 1.0, an open-source explainable AI library for scientific and biomedical applications, and of an end-to-end pipeline for predicting response to anticancer drugs from transcriptomics data (TRL 3 to TRL 5).

Industrial collaboration with Accenture

• Evaluation metrics for the outputs of explainable AI methods for large language models.

Industrial collaboration with Helen Oy and House of AI

• Machine learning and data analysis for the energy sector, with a focus on district-heating time series and consumption forecasting.

MLDB — Model Management Systems, Machine Learning meets Database Systems (Academy of Finland)

• Integrating machine learning functionality into database management systems; contributed to the development of the algorithmic methods.

Co-organizer, 1st Workshop on Generative AI for Social Good and Vulnerable Populations (GenAI4SG) at ACM CIKM 2026

Guest Editor, special issue "Generative AI for Vulnerable and Underserved Populations", Information Processing & Management (Elsevier)

Session Chair, "Large Language Models and AI in Biology and Medicine", ECML PKDD 2026

Program Committee member, workshops at ECML PKDD 2026 (XKDD, SHIELD-AI, SAI4OID)

Co-organizer, ILLUME-4-Science project kick-off event, Pisa

Organizer, reading group on agentic AI, Pisa

Reviewer for conferences including KDD, AAAI and ECML PKDD, and journals including JMLR, DMKD and IEEE TKDE

ECML PKDD 2026, Naples — Virgil: Navigating Explainability for Transformer-based Language Models (oral and demo)

KDD 2026, Jeju Island — Explainable AI for Cancer Drug Response Prediction: Beyond Univariate Feature Attributions (poster)

ECML PKDD 2025, Porto — Sample and Expand: Discovering Low-Rank Submatrices With Quality Guarantees (oral and poster)

International Artificial Intelligence Summer School (IAISS 2025), Castiglione della Pescaia — Explainable AI for Science (poster)

ECML PKDD 2024, Vilnius — The Hadamard Decomposition Problem (oral and poster)

KDD 2024, Barcelona — Efficient Exploration of the Rashomon Set of Rule-Set Models (oral and poster)

Invited seminar, CENTAI Institute, Turin — Efficient and Trustworthy Methods for Knowledge Discovery

ICDM 2022, Orlando — Concise and Interpretable Multi-Label Rule Sets (oral)

SIGMOD 2022 — SIEVE: A Space-Efficient Algorithm for Viterbi Decoding (oral, remote)

EDBT 2022 — Workload-Aware Materialization of Junction Trees (oral, remote)

Guest lecture on large language models, Blockchain e Intelligenza Artificiale — University of Pisa

Guest lecture on interpretability and explainability of large language models, Explainable Artificial Intelligence — Scuola Normale Superiore

Guest lectures (temporal and social networks), Methods of Data Mining — Aalto University

Teaching assistant, Methods of Data Mining — Aalto University

Supervision of one MSc and two BSc theses at Aalto University; co-supervision of an ongoing MSc thesis at the University of Pisa and Scuola Normale Superiore