Ph.Darya Shramko

Alessandro Fabris (he/him)

University of Trieste (UniTs), Italy
Assistant Professor (RTT)

alessandro dot fabris at units dot it

Google Scholar
LinkedIn

I am an 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 disciplines and using mixed methods to tackle complex socio-technical questions. I feel fortunate to collaborate with scholars from a variety of fields. If you're interested in working together, feel free to reach out! I'm currently especially engaged with the AI Act and its practical implementation.

Previously, I spent four years in industry at IBM and Electrolux and two years at he Max Planck Institute for Security and Privacy, where I was advised by Asia Biega. My goal is to support responsible computing by translating policy into actionable practices that practitioners can understand and apply.

News

I am serving as a tutorial chair at FAccT 2025.

I joined 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]

Plain Academic