L-DIH Talks | From data to digital twins: bridging AI and process understanding
Digital Twins provide that bridge: dynamic virtual representations that integrate experimental data, mathematical models, and AI to monitor, predict, and enhance system behaviour in real time.
13/03/2026
Videos
The webinar presented digital twins as a dynamic bridge between experimental data, mathematical models, and AI, enabling real-time monitoring, prediction, and enhancement of system behaviour. The session explored how digital twins are reshaping the way we understand, monitor, and optimise complex industrial environments.
Here’s what we covered:
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Digital twins were presented as dynamic virtual replicas that fuse experimental data, physics-based models, and AI to monitor, predict, and improve system behaviour in real time.
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Recent advances from the Luxembourg Institute of Science and Technology (LIST) showed how AI, physics-informed modelling, and live data converge to deliver reliable and interpretable twins for industrial processes.
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Methodology covered included designing and validating twins with both experimental and simulated data, and combining AI with equation-based models to produce robust predictive intelligence.
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Industrial applications highlighted spanned materials processing, reactive flows, and smart manufacturing, focusing on continuous monitoring, performance forecasting, and operational optimisation.