Published in AIAA SCITECH 2022 Forum, 2022
Recommended citation: I. Zanardi, S. Venturi, and M. Panesi. "Towards Efficient Simulations of Non‑Equilibrium Chemistry in Hypersonic Flows: A Physics‑Informed Neural Network Framework". In: AIAA SCITECH 2022 Forum. American Institute of Aeronautics and Astronautics, Jan. 2022. doi: 10.2514/6.2022-1639.
Published in AIAA SCITECH 2023 Forum, 2023
Recommended citation: I. Zanardi, S. Venturi, A. Munafó, and M. Panesi. "Towards Efficient Simulations of Non‑Equilibrium Chemistry in Hypersonic Flows: Neural Operator‑Enhanced 1‑D Shock Simulations". In: AIAA SCITECH 2023 Forum. American Institute of Aeronautics and Astronautics, Jan. 2023. doi: 10.2514/6.2023-1202.
Published in Physical Chemistry Chemical Physics, 2023
Recommended citation: M. S. Priyadarshini, S. Venturi, I. Zanardi, and M. Panesi. "Efficient quasi‑classical trajectory calculations by means of neural operator architectures". In: Physical Chemistry Chemical Physics 25 (May 2023). doi: 10.1039/D2CP05506F.
Published in Scientific Reports, 2023
Recommended citation: I. Zanardi, S. Venturi, and M. Panesi. "Adaptive physics‑informed neural operator for coarse‑grained non‑equilibrium flows". In: Scientific Reports 13 (Sept. 2023), doi: 10.1038/s41598-023-41039-y.
Published in AIAA SCITECH 2024 Forum, 2024
Recommended citation: I. Zanardi, S. Venturi, and M. Panesi. "Towards Efficient Simulations of Non‑Equilibrium Chemistry in Hypersonic Flows: Application of Neural Operators in Multidimensional CFD Simulations". In: AIAA SCITECH 2024 Forum. American Institute of Aeronautics and Astronautics, Jan. 2024. doi: 10.2514/6.2024-0773.
Published in Journal of Computational Physics, 2024
Recommended citation: C. Jacobsen, I. Zanardi, S. Bhola, K. Duraisamy, and M. Panesi. "Information theoretic clustering for coarse‑grained modeling of non‑equilibrium gas dynamics". In: Journal of Computational Physics 507 (2024). doi: 10.1016/j.jcp.2024.112977.
Published in NeurIPS, 2024
Recommended citation: I. Zanardi, A. N. Diaz, S. W. Chung, M. Panesi, and Y. Choi. Scalable nonlinear manifold reduced order model for dynamical systems. Nov. 2024. doi: 10.48550/arXiv.2412.00507.
Published in AIAA SCITECH 2025 Forum, 2025
Recommended citation: I. Zanardi, A. Padovan, D. J. Bodony, and M. Panesi. "Petrov‑Galerkin Model Reduction for Thermochemical Nonequilibrium Gas Mixtures: Application to the N2+N System". In: AIAA SCITECH 2025 Forum. American Institute of Aeronautics and Astronautics, Jan. 2025. doi: 10.2514/6.2025-2524.
Published in Journal of Computational Physics, 2025
Recommended citation: I. Zanardi, A. Padovan, D. J. Bodony, and M. Panesi. "Petrov‑Galerkin model reduction for thermochemical nonequilibrium gas mixtures". In: Journal of Computational Physics 533 (Apr. 2025), doi: 10.1016/j.jcp.2025.113999.
Published in arXiv, 2025
Recommended citation: Y. Choi, S. W. Cheung, Y. Kim, P.‑H. Tsai, A. N. Diaz, I. Zanardi, S. W. Chung, D. M. Copeland, C. Kendrick, W. Anderson, T. Iliescu, and M. Heinkenschloss. Defining Foundation Models for Computational Science: A Call for Clarity and Rigor. May 2025. doi: 10.48550/arXiv.2505.22904.
Published in arXiv, 2025
Recommended citation: I. Zanardi, A. Meini, A. Padovan, D. J. Bodony, and M. Panesi. Petrov‑Galerkin model reduction for collisional‑radiative argon plasma. June 2025. doi: 10.48550/arXiv.2506.05483.
Published in arXiv, 2025
Recommended citation: I. Zanardi, S. Venturi, and M. Panesi. MENO: Hybrid Matrix Exponential-based Neural Operator for Stiff ODEs. Application to Thermochemical Kinetics. July 2025. doi: 10.48550/arXiv.2507.14341.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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