Alessandro GabbanaDirector's Postdoct Fellow
CNLS/CCS-2 Computational multiscale transport phenomena 
Office: TA-3, Bldg 1690, Room 117
Mail Stop: B284
Phone: (505) 000-0000
Fax: (505) 665-2659
Email: agabbana@lanl.gov
home page Research highlight- V.E. Ambruş, L. Bazzanini, A. Gabbana, D. Simeoni, S. Succi, R. Tripiccione. Fast kinetic simulator for relativistic matter, Nature Computational Science 2 (10), 641-654 (2022).
- A. Gabbana, F. Toschi, P. Ross, A. Haans, A. Corbetta. Fluctuations in pedestrian dynamics routing choices, PNAS nexus 1 (4), pgac169 (2022).
- L.R. Weih, A. Gabbana, D. Simeoni, L. Rezzolla, S. Succi, R. Tripiccione. Beyond moments: relativistic lattice Boltzmann methods for radiative transport in computational astrophysics, Monthly Notices of the Royal Astronomical Society 498 (3), 3374-3394. (2020).
- A. Gabbana, D. Simeoni, S. Succi, R. Tripiccione. Relativistic lattice Boltzmann methods: Theory and applications, Physics Reports 863, 1-63 (2020).
- A. Gabbana, M. Polini, S. Succi, R. Tripiccione, F.M.D. Pellegrino. Prospects for the detection of electronic preturbulence in graphene, Physical Review Letters 121 (23), 236602 (2018).
- E. Calore, A. Gabbana, J. Kraus, E. Pellegrini, S.F. Schifano, R. Tripiccione. Massively parallel lattice–Boltzmann codes on large GPU clusters, Parallel Computing 58, 1-24 (2016).
|  | Educational Background/Employment:- Ph.D. (2019) EJD: Physics, University of Ferrara, Italy - Applied Mathematics, University of Wuppertal, Germany
- M.Sc. (2015) Computational Science and Engineering, Umeå University, Sweden
- B.Sc. (2013) Computer Science, University of Ferrara, Italy
- Employment:
- 2024-present Director's Postdoctoral Resesarch Associate, Los Alamos National Laboratory, Los Alamos, NM, USA.
- 2020-2024 Postdoctoral Research Associate, Eindhoven University of Technology, Eindhoven, The Netherlands.
- 2019-2020 Postdoctoral Research Associate, University of Ferrara, Ferrara, Italy.
Research Interests: - Computational fluid dynamics
- Kinetic Theory
- Scale-bridging
- Physics-informed machine learning
- High-performance computing
Selected Recent Publications: Full list: Google Scholar
- G. Ortali, A. Gabbana, I. Atmodimedjo, A. Corbetta. Enhancing lattice kinetic schemes for fluid dynamics with Lattice-Equivariant Neural Networks, arXiv preprint arXiv:2405.13850 (2024).
- G. Ortali, A. Gabbana, N. Demo, G. Rozza, F. Toschi. Kinetic data-driven approach to turbulence subgrid modeling, arXiv preprint arXiv:2403.18466 (2024).
- F. Klass, A. Gabbana, A. Bartel. Characteristic boundary condition for thermal lattice Boltzmann methods, Computers & Mathematics with Applications 157, 195-208 (2024).
- C.A.S. Pouw, A. Corbetta, A. Gabbana, C. van der Laan, F. Toschi. High-statistics pedestrian dynamics on stairways and their probabilistic fundamental diagrams, Transportation research part C: emerging technologies 159, 104468 (2024).
- A. Corbetta, A. Gabbana, V. Gyrya, D. Livescu, J. Prins, F. Toschi. Toward learning Lattice Boltzmann collision operators, The European Physical Journal E vol. 46, num. 10 (2023).
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