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Anna Ivagnes

Post-doctoral researcher @ SISSA (Trieste, Italy)

  • About Me

    I'm a post-doctoral researcher in the SISSA mathLab group, based in Trieste (Italy). Currently working on data-driven stabilization and filtering approaches to enhance the simulations of convection-dominated flows. Photo

    Education

    SISSA - Trieste (Italy)

    Post-doctoral research contract

    Working on stabilization/closure/filtering approaches for CFD simulations under the supervision of Prof. Gianluigi Rozza (SISSA). Special focus on reinforcement learning strategies and reduced order modeling.

    SISSA - Trieste (Italy)

    PhD in Mathematical Analysis, Modeling and Applications

    Working on stabilization/closure/filtering approaches for CFD simulations under the supervision of Prof. Gianluigi Rozza (SISSA) and Dr. Giovanni Stabile (University of Urbino and Scuola Superiore Sant'Anna, Pisa).

    SISSA - Trieste (Italy)

    Research fellowship

    Research activity in cooperation with FINCANTIERI S.P.A. on the development of a shape optimization pipeline for marine propellers using reduced order models. The project was under the supervision of Nicola Demo and Prof. Gianluigi Rozza.

    PoliTo - Torino (Italy)

    Master degree in Mathematical Engineering

    Master thesis: "Data Enhanced Reduced Order Models for turbulent flows" under the supervision of Dr. Giovanni Stabile, Dr. Andrea Mola, Prof. Traian Iliescu, and Prof. Gianluigi Rozza, and Prof. Claudio Canuto.

    Final mark: 110/110 with honors

    University of Salento - Lecce (Italy)

    Bachelor degree in Industrial Engineering

    Bachelor thesis: "Self-healing materials: study of a cohesive zone model using a thermodynamic approach", under the supervision of Dr. Marco Trullo and Prof. Rossana Dimitri.

    Final mark: 110/110 with honors

    - Liceo Quinto Ennio, Gallipoli - Lecce (Italy)

    Scientific High School

    Final mark: 100/100 with honors

    Research Projects

    Filtering Strategies

    Reduced Order Models & Stabilization

    Nonlinear Reduced Order Models

    Academic Service & Community Engagement

    President of Young-SIMAI (Jan 2026-Now)

    Promoting scientific exchange and collaboration among young researchers in applied mathematics.

    Organization of YMMOR25 (Young Mathematicians in Model Order Reduction) Conference

    Involved in the organization of the YMMOR25 conference, held at SISSA, May 4-9, 2025.

    Officer of the SISSA SIAM Student Chapter (2023-2025)

    Leading activities to promote applied mathematics, scientific computing, and networking among students and early-career researchers.

    Publications

    PhD thesis · 2026

    From Filtering to Data-Driven Closures: Stabilization Strategies for Convection-dominated Flow Simulations

    Anna Ivagnes

    Stabilization strategies for convection-dominated flows, spanning adaptive filtering, data-driven reduced-order models, and nonlinear operator compression.

    Read the PhD thesis on SISSA IRIS

    Preprint, 2026

    A Nonlinear Physics-based Reduced Order Model with Convolutional-based Operator Compression.

    A. Ivagnes, G. Stabile, G. Rozza

    arXiv bibTex

    Preprint, 2026

    Reinforcement Learning-Based Filters for Convection-Dominated Flows: Reference-Free and Reference-Guided Training.

    A. Ivagnes, M. Strazzullo, G. Rozza

    arXiv bibTex

    Preprint, 2026

    Efficient and Accurate Surrogate Modeling of Turbulent Flows via Space-Dependent Aggregation and Reduced Order Models

    P. Zappi, A. Ivagnes, N. Tonicello, G. Rozza

    arXiv bibTex

    Computer Methods in Applied Mechanics and Engineering, 2026

    StabOp: A Data-Driven Stabilization Operator for Reduced Order Modeling

    P. H. Tsai, A. Ivagnes, A. Quaini, T. Iliescu, G. Rozza

    arXiv doi bibTex

    Computer Methods in Applied Mechanics and Engineering, 2026

    A new data-driven energy-stable evolve-filter-relax model for turbulent flow simulation

    A. Ivagnes, T. V. Gastelen, S. D. Agdestein, B. Sanderse, G. Stabile, G. Rozza

    arXiv doi bibTex

    SIAM Scientific Computing, 2026

    Machine Learning-based quadratic closures for non-intrusive Reduced Order Models

    G. Codega, A. Ivagnes, N. Demo, G. Rozza

    arXiv doi bibTex

    Emerging Technologies in Computational Sciences for Industry, Sustainability and Innovation: Math to Product, 2025

    in Computational Fluid Dynamics: An Overview of Methods

    A. Ivagnes, M. Khamlich, P. Siena, G. Rozza

    doi bibTex

    Computer Methods in Applied Mechanics and Engineering, 2025

    Data-driven Closure Strategies for Parametrized Reduced Order Models via Deep Operator Networks

    A. Ivagnes, G. Stabile, G. Rozza

    arXiv doi bibTex

    International Journal of Numerical Methods in Engineering, 2026

    Data‐Driven Optimization for the Evolve‐Filter‐Relax Regularization of Convection‐Dominated Flows

    A. Ivagnes, M. Strazzullo, M. Girfoglio, T. Iliescu, G. Rozza

    arXiv doi bibTex

    Preprint, 2024

    Parametric Intrusive Reduced Order Models enhanced with Machine Learning Correction Terms

    A. Ivagnes, G. Stabile, G. Rozza

    arXiv bibTex

    Acta Mechanica, 2024

    Enhancing non-intrusive Reduced Order Models with space-dependent aggregation methods

    A. Ivagnes, N. Tonicello, P. Cinnella, G. Rozza

    arXiv doi bibTex

    International Journal of Numerical Methods in Engineering, 2024

    A shape optimization pipeline for marine propellers by means of reduced order modeling techniques

    A. Ivagnes, N. Demo, G. Rozza

    arXiv doi bibTex

    Journal of Open Source Software, 2023

    Physics-informed neural networks for advanced modeling

    D. Coscia, A. Ivagnes, N. Demo, G. Rozza

    doi bibTex

    Applied Mathematics and Computation, 2023

    Hybrid data-driven closure strategies for reduced order modeling

    A. Ivagnes, G. Stabile, A. Mola, T. Iliescu, G. Rozza

    arXiv doi bibTex

    Journal of Computational Physics, 2023

    Pressure data-driven variational multiscale reduced order models

    A. Ivagnes, G. Stabile, A. Mola, T. Iliescu, G. Rozza

    arXiv doi bibTex

    Journal of Scientific Computing, 2023

    Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation

    A. Ivagnes, N. Demo, G. Rozza

    arXiv doi bibTex

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