Ricardo Vinuesa

Orcid: 0000-0001-6570-5499

According to our database1, Ricardo Vinuesa authored at least 53 papers between 2019 and 2024.

Collaborative distances:



In proceedings 
PhD thesis 


On csauthors.net:


Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks.
Expert Syst. Appl., 2024

AI in Space for Scientific Missions: Strategies for Minimizing Neural-Network Model Upload.
CoRR, 2024

Enhancing Graph U-Nets for Mesh-Agnostic Spatio-Temporal Flow Prediction.
CoRR, 2024

Opportunities for machine learning in scientific discovery.
CoRR, 2024

Indirectly Parameterized Concrete Autoencoders.
CoRR, 2024

Auto-tuning Multi-GPU High-Fidelity Numerical Simulations for Urban Air Mobility.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

Beyond the Buzz: Strategic Paths for Enabling Useful NISQ Applications.
Proceedings of the 21st ACM International Conference on Computing Frontiers, 2024

Improving the Learning of Mechanics Through Augmented Reality.
Technol. Knowl. Learn., March, 2023

Higher-order dynamic mode decomposition on-the-fly: A low-order algorithm for complex fluid flows.
J. Comput. Phys., February, 2023

From fear to action: AI governance and opportunities for all.
Frontiers Comput. Sci., 2023

Active flow control for three-dimensional cylinders through deep reinforcement learning.
CoRR, 2023

Easy attention: A simple self-attention mechanism for Transformers.
CoRR, 2023

Discovering Causal Relations and Equations from Data.
CoRR, 2023

β-Variational autoencoders and transformers for reduced-order modelling of fluid flows.
CoRR, 2023

Effective control of two-dimensional Rayleigh-Bénard convection: invariant multi-agent reinforcement learning is all you need.
CoRR, 2023

Closing the gap between research and projects in climate change innovation in Europe.
CoRR, 2023

The transformative potential of machine learning for experiments in fluid mechanics.
CoRR, 2023

Explaining wall-bounded turbulence through deep learning.
CoRR, 2023

Get Out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst.
J. Supercomput., 2022

Innovative software systems for managing the impact of the COVID-19 pandemic.
Softw. Pract. Exp., 2022

Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection.
Sensors, 2022

The Role of Robotics in Achieving the United Nations Sustainable Development Goals - The Experts' Meeting at the 2021 IEEE/RSJ IROS Workshop [Industry Activities].
IEEE Robotics Autom. Mag., 2022

Enhancing computational fluid dynamics with machine learning.
Nat. Comput. Sci., 2022

An uncertainty-quantification framework for assessing accuracy, sensitivity, and robustness in computational fluid dynamics.
J. Comput. Sci., 2022

Applying Bayesian optimization with Gaussian process regression to computational fluid dynamics problems.
J. Comput. Phys., 2022

Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula.
J. Artif. Intell. Res., 2022

Modeling the Turbulent Wake Behind a Wall-Mounted Square Cylinder.
Log. J. IGPL, 2022

Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows.
Expert Syst. Appl., 2022

Emerging Trends in Machine Learning for Computational Fluid Dynamics.
Comput. Sci. Eng., 2022

The Sustainable Development Goals and Aerospace Engineering: A critical note through Artificial Intelligence.
CoRR, 2022

Improving aircraft performance using machine learning: a review.
CoRR, 2022

Physics-Informed Transfer Learning Strategy to Accelerate Unsteady Fluid Flow Simulations.
CoRR, 2022

Physics-informed deep-learning applications to experimental fluid mechanics.
CoRR, 2022

Predicting the temporal dynamics of turbulent channels through deep learning.
CoRR, 2022

The potential of artificial intelligence for achieving healthy and sustainable societies.
CoRR, 2022

Understanding the Bibliometric Patterns of Publications in IEEE Access.
IEEE Access, 2022

Data deprivations, data gaps and digital divides: Lessons from the COVID-19 pandemic.
Big Data Soc., July, 2021

Interpretable deep-learning models to help achieve the Sustainable Development Goals.
Nat. Mach. Intell., 2021

Acquisition and User Behavior in Online Science Laboratories before and during the COVID-19 Pandemic.
Multimodal Technol. Interact., 2021

UQit: A Python package for uncertainty quantification (UQ) in computational fluid dynamics (CFD).
J. Open Source Softw., 2021

Aim in Climate Change and City Pollution.
CoRR, 2021

The Potential of Machine Learning to Enhance Computational Fluid Dynamics.
CoRR, 2021

Assessments of model-form uncertainty using Gaussian stochastic weight averaging for fluid-flow regression.
CoRR, 2021

Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations.
CoRR, 2021

COVID-19 Digital Contact Tracing Applications and Techniques: A Review Post Initial Deployments.
CoRR, 2021

Towards and Ethical Framework in the Complex Digital Era.
CoRR, 2020

A socio-technical framework for digital contact tracing.
CoRR, 2020

Recurrent neural networks and Koopman-based frameworks for temporal predictions in turbulence.
CoRR, 2020

On the use of recurrent neural networks for predictions of turbulent flows.
CoRR, 2020

The role of artificial intelligence in achieving the Sustainable Development Goals.
CoRR, 2019

Soft Computing Techniques to Analyze the Turbulent Wake of a Wall-Mounted Square Cylinder.
Proceedings of the 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), 2019

Distributed Percolation Analysis for Turbulent Flows.
Proceedings of the 9th IEEE Symposium on Large Data Analysis and Visualization, 2019