Neil Ashton

WW Tech Lead for Computer-Aided Engineering (CAE) Amazon Web Services

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I’m the WW Tech Leader for CAE at Amazon Web Services and also act as one of the main subject-matter experts for Computational Fluid Dynamics, High Performance Computing (HPC) and AI/ML for CFD across Amazon. I am also a Fellow of the Institution of Mechanical Engineers. Previous to these positions I worked in Formula 1 with the Lotus F1 team (now Renault F1) and I worked with Formula 1 Management and the FIA on the 2021 technical regulation changes and I was also a core part of the British Cycling 2020 Tokyo Olympics bike development program. I’m passionate about explaining science and engineering to the general public and also host a podcast which you can listen on Spotify or watch on YouTube.

news

Aug 22, 2024 A new paper showing a large-scale high-fidelity DrivAer-based ML training datasets is now available on arxiv DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics
Aug 08, 2024 Two new papers on arxiv, focusing on new ML training datasets.WindsorML: High-Fidelity Computational Fluid Dynamics Dataset for Automotive Aerodynamics and AhmedML: High-Fidelity Computational Fluid Dynamics Dataset for Incompressible, Low-Speed Bluff Body Aerodynamics
Jul 28, 2024 Two new papers published at AIAA Aviation 2024. Immersed Boundary Wall-Modelled Large Eddy Simulations for Automotive Aerodynamics and Assessing the HPC performance of CODA for the NASA Common Research Model.
Jul 22, 2024 Latest Neil Ashton podcast episode with Prof Karthik Duraisamy. You can listen on Spotify or watch on YouTube.
Jul 09, 2024 Latest Neil Ashton podcast episode with Prof Max Welling. You can listen on Spotify or watch on YouTube.

selected publications

  1. drivaerml.png
    DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics
    Neil Ashton , Charles Mockett , Marian Fuchs , and 9 more authors
    arxiv.org, 2024
  2. ahmedml.png
    AhmedML: High-Fidelity Computational Fluid Dynamics Dataset for Incompressible, Low-Speed Bluff Body Aerodynamics
    Neil Ashton , Danielle Maddix , Samuel Gundry , and 1 more author
    arxiv.org, 2024
  3. windsorml.png
    WindsorML: High-Fidelity Computational Fluid Dynamics Dataset for Automotive Aerodynamics
    Neil Ashton , Jordan Angel , Aditya Ghate , and 6 more authors
    arxiv.org, 2024
  4. 2024ml.png
    Machine Learning for Road Vehicle Aerodynamics
    Vidyasagar Ananthan , Neil Ashton , Nate Chadwick , and 9 more authors
    In SAE World Congress , 2024
  5. highlift.png
    Summary of the 4th High-Lift Prediction Workshop Hybrid RANS/LES Technology Focus Group
    Neil Ashton , Paul Batten , Andrew Cary , and 1 more author
    Journal of Aircraft, Aug 2023
  6. drivaer.png
    Towards a Standardized Assessment of Automotive Aerodynamic CFD Prediction Capability - AutoCFD 2: Ford DrivAer Test Case Summary
    Burkhard Hupertz , Neil Lewington , Charles Mockett , and 2 more authors
    In SAE Technical Papers , Mar 2022
  7. hpc.png
    Performance of cpu and gpu hpc architectures for off-design aircraft simulation
    M. Turner , J. Appa , and N. Ashton
    In AIAA Scitech 2021 Forum , Mar 2021
  8. assess.png
    Assessment of RANS and DES methods for realistic automotive models
    N. Ashton , A. West , S. Lardeau , and 1 more author
    Computers & Fluids, Mar 2016