HeyJaredThe Neil Ashton Podcast
This podcast focuses on explaining the fascinating ways that science and engineering change the world around us.
- Indexed episodes, last 90 days
- 4
- Latest publication
- Aug 29, 2026
- Audience
- Checking…
- Earliest in this view
- Jul 9, 2026
Latest episodes
S4 EP7 - Should You Still Study Engineering in the Age of AI? (opens the original)
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Should you still study engineering when AI can already write code, analyse data and automate parts of an engineer's job? In this solo episode, Neil Ashton gives his view on engineering education and careers in the age of AI. His answer is yes—but the skill set is changing. Neil explains why engineering fundamentals still matter, where AI can act as an enabler, what students and early-career engineers should learn now, and why soft skills, projects and internships may become even more important.
S4 EP6 - Daniel Mira on Hydrogen Combustion Modelling and Future Propulsion (opens the original)
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Hydrogen combustion, high-fidelity CFD and the future of aircraft propulsion are the focus of this conversation with Dr. Daniel Mira, Head of the Propulsion Technologies Group at the Barcelona Supercomputing Center. Neil and Dani discuss why reacting flows are so difficult to simulate, how hydrogen changes combustion and aircraft design, the limits of RANS, LES and DNS, GPU-native solvers, coding agents and AI surrogate models. Full episode, corrected transcript and resources: https://neilashton
S4 EP5 - Prof. Nils Thuerey on Differentiable Physics and Foundation Models (opens the original)
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Differentiable physics, neural emulators and foundation models for PDEs are the focus of this conversation with Professor Nils Thuerey, head of the Physics-based Simulation group at TUM. Neil and Nils discuss PhiFlow, PICT, Tadpole, scalable 3D transformers, online synthetic data, open datasets, world models and agents that call physics simulators. Full episode, corrected transcript and resources: https://neilashton.co.uk/podcasts/s4-e5-prof-nils-thuerey-on-differentiable-physics-and-foundation-
S4 EP4 - Prof. Paola Cinnella on AI for Science and Fluid Mechanics (opens the original)
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RANS uncertainty, data-driven turbulence modeling and AI for Science are the focus of this conversation with Professor Paola Cinnella, Professor of Fluid Mechanics at Sorbonne University and Director of SCAI. Neil and Paola discuss high-order methods, dense gases, Bayesian uncertainty, AirfRANS, surrogate modeling, scientific publishing and education in the AI era. Full episode, corrected transcript and resources: https://neilashton.co.uk/podcasts/s4-e4-prof-paola-cinnella-on-ai-for-science-and-
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