activity
20222026
most citedImproving aircraft performance using machine learning: a review

194 citations · 215 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Low-Cost High-Order Singular Value Decomposition for Tensor-Based Reconstruction from Sparse Sensor Measurements: Urban Flow and Air-Quality Applications

Arindam Sengupta, Paul Jeanney, Ricardo Vinuesa +2

Urban flow and air-quality simulations generate high-dimensional datasets describing velocity and pollutant transport across multiple spatial, temporal, and physical-variable dimen…

cs.LG2026

GenDA: Generative Data Assimilation on Complex Urban Areas via Classifier-Free Diffusion Guidance

Francisco Giral, Álvaro Manzano, Ignacio Gómez +2

Urban wind flow reconstruction is essential for assessing air quality, heat dispersion, and pedestrian comfort, yet remains challenging when only sparse sensor data are available.…

cs.RO2024

Transformer-Based Fault-Tolerant Control for Fixed-Wing UAVs Using Knowledge Distillation and In-Context Adaptation

Francisco Giral, Ignacio Gómez, Ricardo Vinuesa +1

This study presents a transformer-based approach for fault-tolerant control in fixed-wing Unmanned Aerial Vehicles (UAVs), designed to adapt in real time to dynamic changes caused…

cs.LG2022★ 194 cited

Improving aircraft performance using machine learning: a review

Soledad Le Clainche, Esteban Ferrer, Sam Gibson +3

This review covers the new developments in machine learning (ML) that are impacting the multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics (expe…

physics.flu-dyn2022★ 21 cited

Data-driven assessment of arch vortices in simplified urban flows

Álvaro Martínez-Sánchez, Eneko Lazpita, Adrián Corrochano +3

Understanding flow structures in urban areas is widely recognized as a challenging concern due to its effect on urban development, air quality, and pollutant dispersion. In this st…