Get Better, Faster Simulations - Without Needing to Be a Machine Learning Expert

Machine learning doesn’t just solve moonshot problems — it can also help with the practical challenges fusion scientists and engineers face every day.

 

In this workshop, our digiLab Fusion experts will show you how to apply intelligent, uncertainty-aware ML methods to reduce your simulation workload while improving the quality and relevance of your results. Whether you're running design studies, sensitivity analyses, or integrated models, this session will show you how to get up to 10× faster convergence without sacrificing rigour.

Workshop Overview

What You'll Learn From Our 

Fusion Experts

1. How machine learning can help you choose simulation inputs more intelligently.

2. How to build ML models you can trust using uncertainty quantification.

3. How our low-code platform, the Uncertainty Engine, makes these tools accessible to everyone.

How This Will Improve 

Your Simulation Workflow

1. Fewer simulations needed to answer complex technical questions.

2. More converged simulations more often

3. Greater relevance and insight in your results.

4. No prior ML experience required - just bring your domain expertise.

Who Should Attend?

This session is ideal for fusion professionals and engineers looking to maximise their simulation efforts:

- Plasma Physicists

- Integrated Modellers

- Neutronics Engineers

- Thermal/Structural Engineers

- Computational Scientists

- Nuclear Simulation Engineers

- Model-Based Systems Engineers

- Anyone exploring ML in high-stakes physics and engineering contexts

Meet Our Fusion Experts

Cyd Cowley 

digiLab Solution Engineer (Fusion)

Dan Greenhouse

digiLab Solution Engineer (Fusion)

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