Alessandro Fabris

I am an incoming assistant professor (tenure track -- RTT) of computer science at the University of Trieste. I study algorithmic fairness and auditing of artificial intelligence systems. My research centers on defining, operationalizing, and measuring fairness, with a focus on domain-specific requirements, and a critical perspective on data management and ethics.

I enjoy working across domains and leveraging mixed methods for complex socio-technical questions. I am lucky to work across disciplinary boundaries with scholars from different fields. Get in touch if you're interested in collaborating! Currently, I am especially interested in the AI Act and its implementation.

Previously, I spent four years in industry with IBM and Electrolux and two years with Max Planck Institute for Security and Privacy, advised by Asia Biega. To develop relevant solutions for pressing socio-technical issues, I aim to guide and translate policy into responsible computing practices that practitioners can understand and adopt.

News

I am serving as a tutorial chair at FAccT 2025.

In March 2025 I am joining the Univesrity of Trieste as a tenure-track assistant professor.

The 3rd European Workshop on Algorithmic Fairness took place in Mainz, Germany, on July 1-3, 2024. See you next year at EWAF'25!

I have been granted a Humboldt Research Fellowship to study algorithmic fairness with limited data.

My Ph.D. thesis received the Elena Cornaro Award for gender studies.

We advised five AI providers on compliance at the EU AI Act Grand Challenge.

Our research on discrimination in car insurance was featured on national TV (Rai3) and international press (AlgorithmWatch).

The 2nd European Workshop on Algorithmic Fairness took place in June 2023 and I was a Program Chair. We had a really exciting program (if I may say so myself)!

Our book on quantification is out. Have a look if you're interested in estimators for groups rather than individuals.

I successfully defended my Ph.D. I am now a postdoctoral researcher at Max Planck Institute for Security and Privacy.

I received the IP&M Best Ph.D. Paper Award.

Selected publications

Multi-Label Continual Learning for the Medical Domain: A Novel Benchmark
Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris, Gian Antonio Susto
(WACV 2025) The IEEE/CVF Winter Conference on Applications of Computer Vision, to appear
[upcoming]

Fairness and Bias in Algorithmic Hiring: a Multidisciplinary Survey
Alessandro Fabris, Nina Baranowska, Matthew J. Dennis, David Graus, Philipp Hacker, Jorge Saldivar, Frederik Zuiderveen Borgesius, Asia J. Biega
(TIST 2025) ACM Transactions on Intelligent Systems and Technology
Cited by the European Parliament Research Service.
MAIEI invited piece.
[PDF] [BIB]

The Venus score for the assessment of the quality and trustworthiness of biomedical datasets
Davide Chicco, Alessandro Fabris, Giuseppe Jurman
(BioData Mining 2025)
[PDF] [BIB]

Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust
Teresa Scantamburlo, Atia Cortés, Francesca Foffano, Cristian Barrué, Veronica Distefano, Long Pham, Alessandro Fabris
(TAI 2024) IEEE Transactions on Artificial Intelligence, to appear
[PDF] [BIB]

Lazy Data Practices Harm Fairness Research
Jan Simson, Alessandro Fabris, Christoph Kern
(FAccT 2024) The 7th ACM Conference on Fairness, Accountability, and Transparency
[PDF] [BIB]

Learning to Quantify
Andrea Esuli, Alessandro Fabris, Alejandro Moreo, Fabrizio Sebastiani
(IRS 2023) The Information Retrieval Series 47, Springer
[PDF] [BIB]

Measuring Fairness Under Unawareness of Sensitive Attributes: A Quantification-Based Approach
Alessandro Fabris, Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani
(JAIR 2023) Journal of Artificial Intelligence Research, vol 76
[PDF] [BIB]

Pairwise Fairness in Ranking as a Dissatisfaction Measure
Alessandro Fabris, Gianmaria Silvello, Gian Antonio Susto, Asia J. Biega
(WSDM 2023) The 16th ACM International Conference on Web Search and Data Mining
[PDF] [BIB]

Algorithmic Fairness Datasets: the Story so Far
Alessandro Fabris, Stefano Messina, Gianmaria Silvello, Gian Antonio Susto
(DAMI 2022) Data Mining and Knowledge Discovery, vol 36
Webapp released.
[PDF] [BIB]

Tackling Documentation Debt: A Survey on Algorithmic Fairness Datasets
Alessandro Fabris, Stefano Messina, Gianmaria Silvello, Gian Antonio Susto
(EAAMO 2022) The 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization
[PDF] [BIB]

Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing
Alessandro Fabris, Alan Mishler, Stefano Gottardi, Mattia Carletti, Matteo Daicampi, Gian Antonio Susto, Gianmaria Silvello
(AIES 2021) The 4th AAAI /ACM Conference on Artificial Intelligence, Ethics, and Society
National and international press coverage.

National TV: Report Rai3.
[PDF] [BIB]

Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms.
Alessandro Fabris, Alberto Purpura, Gianmaria Silvello, Gian Antonio Susto
(IPM 2020) Information Processing & Management, vol 57
IP&M Best Ph.D. Paper Award
[PDF] [BIB]