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Full record. A PDF version is linked at the top.

Contact Information

Name Guido Gagliardi
Professional Title Post-Doctoral Researcher — ESAT-STADIUS, KU Leuven
Email guido.gagliardi@kuleuven.be

Professional Summary

Explainable AI for clinical neurophysiology. Dual PhD with honors (KU Leuven; Universities of Florence, Siena and Pisa, 2026). FWO Strategic Basic Research fellow. Author of PhysioEx and ProtoSleepNet. Italian nationality.

Experience

  • 2026 - Present

    Leuven, Belgium

    Post-Doctoral Researcher
    KU Leuven — ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics
    Explainable deep learning for physiological signals, in the group of Prof. Maarten De Vos.
    • Foundation models for clinical EEG and semantic embeddings for neurophysiological signals.
    • Prototype-based interpretability for sleep staging and sleep-related conditions.
  • 2025 - 2026

    Berlin, Germany

    Visiting Researcher
    Fraunhofer Heinrich Hertz Institute
    Prof. Wojciech Samek’s Artificial Intelligence department, funded by an FWO travel grant.
    • Attribution methods for time-frequency data; the Spectral Gradients line of work.
  • 2021 - 2026

    Leuven, Belgium

    Doctoral Researcher (FWO SBO Fellow)
    KU Leuven — ESAT, STADIUS
    Clinical sleep profiling with UZ Leuven, combining deep learning with concept-based explainability.

Education

  • 2021 - 2026

    Leuven, Belgium

    PhD, with honors
    KU Leuven — Arenberg Doctoral School, Faculty of Engineering Science
    Engineering Science — Explainable Artificial Intelligence
    • Thesis: Explainable Artificial Intelligence: from Model-based to Knowledge-driven Understanding. Supervisor: Prof. Maarten De Vos.
    • Defended 27 May 2026 before a joint jury, as a dual degree with the Italian programme below.
  • 2021 - 2026

    Florence, Italy

    PhD, with honors
    Universities of Florence, Siena and Pisa — joint programme
    Smart Computing
    • Co-supervisor: Prof. Mario G. C. A. Cimino (University of Pisa).
  • 2019 - 2021

    Pisa, Italy

    M.Sc.
    University of Pisa
    Artificial Intelligence and Big Data Engineering
    • Graduated 110/110 cum laude.
    • Thesis: A novel multimodal feature learning architecture for explainable affective computing.
  • 2015 - 2019

    Pisa, Italy

    B.Sc.
    University of Pisa
    Computer Engineering
    • Graduated 105/110.

Funding and grants

  • Approximately €200,000 in competitive personal funding, plus compute allocations on three national and European supercomputers.
  • FWO Strategic Basic Research Fellowship (mandate 1SH4Z24N), Research Foundation Flanders — approximately €131,000, 2023–. Personal four-year fellowship; success rate below 20%.
  • FWO Travel Grant for a Long Research Stay Abroad (mandate V458425N), Research Foundation Flanders — €9,900, 2025. Funded the research stay at Fraunhofer HHI, Berlin.
  • Pegaso Scholarship, Regione Toscana (Giovanisì) — €61,300, 2021–2023.
  • Compute allocations: VSC (Flanders), LUMI (EuroHPC JU) and Leonardo/CINECA — all competitively allocated.
  • Project participation: EXPERIENCE (EU H2020, no. 101017727); FAIR Spoke 1 “Human-Centered AI” (PNRR PE00000013); FoReLab (MIUR Departments of Excellence, University of Pisa); FWO S003524N, G0C9623N and G0D8321N.

Awards

  • 2026
    Dual PhD with honors
    KU Leuven; Universities of Florence, Siena and Pisa

    Awarded to fewer than 5% of candidates.

  • 2023
    FWO Strategic Basic Research Fellowship
    Research Foundation Flanders
  • 2021
    Pegaso Scholarship
    Regione Toscana
  • 2021
    M.Sc. cum laude, 110/110
    University of Pisa

Teaching

  • Guest Lecturer — Explainable and Trustworthy Artificial Intelligence, Ghent University (UGain / VAIA professional course), 2026. Coordinated by Prof. Dr. Femke De Backere. Contributed lectures on explainability and interpretability techniques.
  • Teaching Assistant — Biomedical Signal Processing, KU Leuven, 2021–2026. M.Sc. programmes in Biomedical Engineering and Electrical Engineering: exercise sessions, student support and grading.

Supervision

  • 12 M.Sc. theses supervised at the University of Pisa, 2022–2026 — 10 as principal advisor (relatore), one as co-advisor, one as tutor, with Prof. M. G. C. A. Cimino and Prof. A. L. Alfeo. Day-to-day supervision (problem definition, method, experiments and writing) was mine; Cimino and Alfeo were the formal supervisors.
  • Two students continued to doctoral study: C. Daka (University of Pisa) and I. Grillo (KU Leuven).
  • The full list, with deposited titles and formal roles, is on the research page.

Academic service

  • Submission Chair, IEEE ICAI-TEMS 2026, Pisa, Italy.
  • Reviewer for AAAI 2026 and the Journal of Ambient Intelligence and Humanized Computing (Springer).
  • Member of the Sleep Revolution network (Horizon 2020, grant agreement 965417).

Collaborations

  • Fraunhofer HHI, Berlin — Prof. W. Samek: attribution methods for time–frequency data.
  • Technion and Universidade Federal de Minas Gerais — Prof. J. A. Behar and Prof. A. L. P. Ribeiro: cross-cohort generalisation in physiological time series.
  • University of Copenhagen — Prof. B. R. Kornum: narcoleptic mouse models.
  • Aarhus University, Center for Ear-EEG — J. Strøm: Alzheimer’s disease and REM Sleep Behaviour Disorder.
  • University of Valladolid — Dr. J. Jiménez-García: paediatric sleep apnoea.

Software

  • PhysioEx — PyTorch library for explainable modelling of physiological signals; 12 clinical cohorts behind one interface. Published in Physiological Measurement (2025); on PyPI.
  • ProtoSleepNet — prototype-based interpretable sleep staging across 11 polysomnography datasets and 12,317 subjects, with a live explainability demo.
  • Spectral Gradients — disentangled time–frequency attributions (manuscript in preparation with Prof. W. Samek).

Languages

Italian : Native speaker
English : C1
German : Beginner, currently learning