Welcome to the Aerofluids, Learning & Discovery Lab (ALD Lab). We are part of Galcit at Caltech and AeroAstro at MIT
Announcements
Nov 2025: Our lab presented multiple talks at the APS DFD 2025 Meeting in Houston, TX, sharing the latest advancements in our research. You can check here the abstracts.
Nov 2025: Check our new paper on “Disentangling informative and non-informative dynamics between time signals in chaotic systems” published in Chaos, Solitons and Fractals.
Nov 2025: Check our paper “Bow shock instability at hypersonic speed” associated with our poster winner of the 2024 American Physical Society’s Division of Fluid Dynamics (DFD) Milton van Dyke Award.
Nov 2025: Check our new pre-print on “General-purpose Data-driven Wall Model for Low-speed Flows. Part I: Baseline Model”.
Nov 2025: Adrian gave an invited talk about “Information-theoretic formulation of turbulence” at the Scott Collis Advanced Modeling and Simulations Seminar Series from the University of Texas.
Oct 2025: Check our new paper on “Dimensionless learning based on information” published in Nature Communications, which has been featured on MIT Aeroastro News and Caltech News.
Aug 2025: Check our new pre-print on “Cause-and-effect approach to turbulence forecasting”.
July 2025: Rong won the USNCCM Best Presentation Award at the 18th U.S. National Congress on Computational Mechanics in Chicago for her work on “Machine-learning wall-model large-eddy simulation of low-speed and high-speed flows over rough surfaces”. Congratulations!
June 2025: Álvaro and Adrian participated in the Sixth Madrid Turbulence Workshop at the Polytechnic University of Madrid with the project “Spatio-temporal causal analysis of large-scale motions in wall-bounded turbulence”.
May 2025: Adrian gave an invited talk about “Building-block flow model: An ML-based general-purpose closure model for large-eddy simulation” at the NASA High Fidelity CFD Workshop in the Lockheed Martin Center for Innovation at Suffolk, VA.
View all announcements here.
Featured Publications
Y. Yuan and A. Lozano-Duran, Dimensionless learning based on information, Nat. Commun. 16, 9171 (2025).
Á. Martínez-Sánchez, G. Arranz, A. Lozano-Duran, Decomposing causality into its synergistic, unique, and redundant components, Nat. Commun. 15, 9296 (2024).
G. Arranz, Y. Ling, S. Costa, K. Goc, and A. Lozano-Duran. “Building-block-flow computational model for large-eddy simulation of external aerodynamic applications”, Communications Engineering 3:127, 2024.
A. Lozano-Durán and H. J. Bae, “Machine-learning building-block-flow wall model for large-eddy simulation“, J. Fluid Mech., 963, A35 , 2023.
A. Lozano-Durán, G. Arranz, ’’Information-theoretic formulation of dynamical systems: causality, modeling, and control”, Physical Review Research, 2022.
Y. Yuan and A. Lozano-Duran, Limits to extreme event forecasting in chaotic systems, Physica D., 467, 134246, 2024.
View all publications here.