Daniel Springer, PhD
Head of Data Science & Machine Learning
Daniel holds a PhD in Physics from Nanyang Technological University in Singapore and has a background spanning physics, data science, and machine learning. He focuses on physics-informed and interpretable models for time-series and spatio-temporal data, enabling transparent digital twins and decision-support tools that provide insight into process behaviour and key drivers rather than relying on black-box predictions.
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