Bardh Prenkaj

Bardh Prenkaj

Biography

Currently a postdoc in ML Privacy and Security at the Technical University of Munich.

From 10/2022 to 10/2024, I was a postdoc at Sapienza in anomaly detection and explainability. During this period (June-September 2023), I spent time at my current research group, RDS working on graph counterfactual explainability.

I received my PhD in Computer Science from the Sapienza University of Rome in 2022 with a thesis on “Latent Deep Sequential Learning of Behavioural Sequences”. In Rome, I worked in the AIIM - formerly IIM - group advised by Paola Velardi and Giovanni Stilo. I then worked as a senior researcher at the Department of Computer Science in Sapienza in anomaly detection for social isolation disorders (February - September 2022).

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Interests
  • Anomaly Detection
  • Machine Robustness
  • Machine Unlearning
  • AI for Healthcare
Education
  • PhD in Computer Science, 2022

    Sapienza University of Rome

  • MSc in Computer Science (Grade 110/110 with honors; GPA 4.00, top 1%), 2018

    Sapienza University of Rome

  • BSc in Computer Science (Grade 110/110; GPA 4.00, top 1%), 2016

    Sapienza University of Rome

Positions

  • AI Scientist Jun 2026 – Present
    GaiaLogicRemote
  • Postdoc Apr 2024 – Mar 2026
    Technical University of MunichMunich, Germany
  • Postdoc Oct 2022 – Apr 2024
    Sapienza University of RomeRome, Italy
  • Research Fellow Dec 2021 – Sep 2022
    Sapienza University of RomeRome, Italy
  • Research Assistant Jul 2017 – Oct 2018
    Sapienza University of RomeRome, Italy

Honors & Awards

  • Oct 2026
    🏆 Top Reviewer Award NeurIPS 2026
  • May 2026
    🏆 Golden Reviewer Award ICML 2026
  • Apr 2025
    🎖️ Friedrich Schiedel Fellowship TUM Think Tank (see cohort)
    Won a grant of €20,000 for the project “Game–Theoretic Counterfactual Explainability for Ethical and Transparent AI in Society” (Jun 2025 – Apr 2026).
  • Mar 2025
    🎓 Italian National Scientific Qualification (Habilitation) Italian Ministry of University and Research
    Associate Professor (II Fascia) in the call 2023/2025 (Ministerial Decree n. 1796/2023) for the disciplinary field 01/B1 – Informatics. Valid until 03/2037.
  • Aug 2024
    🏆 Outstanding Reviewer Award KDD 2024
  • Feb 2024
  • Feb 2024
    🎓 Subject Expert Sapienza University of Rome
    (“Cultore della Materia” Art. 42 del R.D. 04/06/1938, n. 1269) Award for highly-skilled researcher and technician on Machine Learning course in M.Sc. CS, Department of CS
  • Dec 2023
    🏆 Highlighted Reviewer NeurIPS XAIA 2023 Workshop
  • Mar 2023
    🎓 Subject Expert University of L’Aquila
    (“Cultore della Materia” Art. 42 del R.D. 04/06/1938, n. 1269) Award for highly-skilled researcher and technician on Deep Neural Networks course in M.Sc. CS, Department of Information Engineering, CS, and Mathematics
  • Nov 2021 – Sep 2022
    🏅 Scholarship in AI & CS Sapienza University of Rome See certificate
  • May 2020 – Apr 2021
  • Jul 2019 – Jul 2019
    📚 3rd International Summer School on Deep Learning IRDTA
    Research training event about the most recent advances in the critical and fast developing area of deep learning
  • Mar 2017
    🏅 Graduation Prize (B.Sc.) LazioDiSU, Ente per il Diritto agli Studi Universitari nel Lazio See certificate
    Winner of the Premio di Laurea distributed from LazioDiSU to excellent bachelor degree students. Winner num: 899, grade: 110/110, Sum: € 2,559.18
  • Sep 2013 – Oct 2018
    🏅 Merit Scholarship in CS LazioDiSU, Ente per il Diritto agli Studi Universitari nel Lazio
    Winner of the LazioDiSU Study Scholarship for B.Sc. (3 years) and M.Sc. (2 years). Yearly sum: € 5,118.36

Recent Publications

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(2026). Co-Recursive Semantic Self-Extension: A Mathematical Foundation for Open-Ended Intelligence. arXiv.

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(2026). Causal Routing for Unlearning. arXiv.

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(2026). High-Dimensional Online Change Point Detection with Adaptive Thresholding and Interpretability. arXiv.

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(2026). Beyond Binary Rewards: A Comparative Study of Reward Design for Reinforcement Unlearning. arXiv.

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(2026). Active Tabular Augmentation via Policy-Guided Diffusion Inpainting. arXiv.

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