Talks
An archive of keynotes, invited seminars, conference sessions, and technical workshops spanning AI for engineering, computational fluid dynamics, and high-performance computing.
2026
- SIGGRAPH 2026 — sponsored keynoteNVIDIA | Next Era of Graphics — Neural Rendering, World Models, and SimulationEvent page
- University of Oxford Mathematical Institute Seminar SeriesTowards a Foundation Model for Computational Engineering: Opportunities, Challenges, and Novel Scaling LawsEvent page
- NASA Ames Seminar SeriesPerspectives on Foundation Models and Agentic Architectures for Computational Fluid DynamicsWatch the seminar
- Sutter Hill Ventures AI Seminar SeriesTowards a Foundation Model for Computational Engineering: Opportunities, Challenges, and Novel Scaling Laws
- UKRI AI4Turbulence WorkshopInvited panel discussion on industry perspectives for AI and turbulence
2025
- Ohio State Aero/Acoustics MIXA Seminar SeriesPerspectives on Foundation Models for Computational Fluid Dynamics
- PASC25Scaling AI Surrogate Modelling Methods Towards Industrial Application for Computational Fluid Dynamics mini-symposium
- ISC25Machine Learning for Computer-Aided Engineering Birds of a Feather session
- NASA High-Fidelity CFD WorkshopEnabling industrially relevant high-fidelity CFD and AI surrogate models for external aerodynamics — invited talk
- 2nd ERCOFTAC Machine Learning for Fluid DynamicsPlenary panel chair and “Detailed assessment of a data-driven GNN approach for the AhmedML, WindsorML and DrivAerML datasets”
2024
- AutoCFD4 AI/ML Technology Focus GroupInitial AutoCFD4 results using the WindsorML and DrivAerML datasets
- 1st ERCOFTAC Machine Learning for Fluid DynamicsOpen-Source Machine Learning Training Dataset for the Windsor Body Using High-Fidelity Cartesian Immersed Boundary WMLES
2023
- F1 and AWS Trackside: The Power of DataWhy do golf balls have dimples? An exploration of aerodynamics and its influence on winning Formula 1 races
- 18th OpenFOAM Conference — keynoteThe role of cloud computing, machine learning, and HPC in accelerating the adoption of high-fidelity CFD for industry
- 22nd International Computational Fluids Conference — invited keynoteThe role of cloud computing, machine learning, and HPC in the advancement of high-fidelity CFD for industry
- NASA Ames Seminar SeriesHow cloud computing, machine learning, and HPC are accelerating adoption of HRLES and WRLES methods for industry
- MIT ACDL Seminar SeriesThe role of cloud computing, machine learning, and HPC in the advancement of high-fidelity CFD for industry
2021
- Aerovehicles International Conference — invited keynoteSummary of the 2nd Automotive CFD Prediction Workshop
- SAE World Congress — invited keynoteThe role of cloud computing and machine learning in next-generation CFD for vehicle aerodynamicists
2020
- NASA Ames Seminar SeriesHigh-Fidelity CFD in the Cloud — Thoughts and PerspectivesEvent page
- 15th OpenFOAM Workshop — keynoteEnabling High-Fidelity CFD on the Cloud through AWS
- Oxford University Aeronautical SocietyTurbulence and Aerodynamics — Enabling a Greener Future
2019
- International Society for Computational Fluid DynamicsTowards High-Fidelity CFD in the Automotive Sector
- University of Oxford Scientific SocietyTurbulence and Aerodynamics — Enabling a Greener Future
- IMechE Simulation and Modelling ConferenceThe Future of CFD in Industry
- Amazon Web ServicesThe Future of CFD and Opportunities for the Cloud
- Gdańsk University of TechnologyIndustrial Hybrid RANS–LES Applications
2018
- Oxford Sparks PodcastStories from the Field
2017
- Airbus DiPaRT 2017Verification and validation of OpenFOAM for high-lift aircraft flows
- Supercomputing 2017 with LenovoImproved aerodynamics using HPC
- ParCFD 2017High-fidelity industrial simulations in OpenFOAM on ARCHER — perspectives on the need for exascale computing
2016
- NAFEMS Hybrid RANS–LES SeminarHybrid RANS–LES, automatic mesh refinement, and HPC considerations
- Oxford Royale Summer SchoolTurbulence and finding a rewarding career in science and engineering
- NASA Ames Seminar SeriesRecent experiences of modelled-stress depletion using DDES and IDDES for the 30P30N three-element aerofoil
- TEDxOxfordTurbulence: Finding Order in Chaos
- High Performance Computing & Big Data Conference — invited talkDeveloping an improved aerodynamic design process for the aerospace and automotive industries using HPC
- Institut de Mécanique des Fluides de ToulouseTowards an entirely virtual design process: the challenge for turbulence modelling
2015
- University of ManchesterEngaging with US academia and industry for aerospace research
- Oxford e-Research CentreTowards an entirely virtual engineering design process: the challenge for turbulence modelling
- Boeing Research & DevelopmentComputational challenges for aerodynamic design in Formula 1
- NASA Ames Research CenterComputational challenges for aerodynamic design in Formula 1
2014
- Gdańsk University of TechnologyEmbedded hybrid RANS–LES approaches
- Scuderia Toro Rosso Formula 1 TeamApplication of elliptic blending models for complex geometries
- NASA Ames Research CenterAn embedded hybrid RANS–LES approach for three-dimensional separated flows
- UCLA Samueli School of EngineeringAn embedded hybrid RANS–LES approach for three-dimensional separated flows
- Barcelona Supercomputing CenterAeroacoustic prediction of a three-element aerofoil using hybrid RANS–LES methods
2013
- University of Oxford Department of Engineering ScienceOverview of recent hybrid RANS–LES developments at the University of Manchester