At Sirris, I work on data-driven innovation projects for industrial and energy-related applications. I help companies leverage their data to improve performance, reliability and decision-making.
My expertise builds on a strong background in mathematics and experience in data analysis, forecasting and optimisation. I develop robust and interpretable AI approaches, with a focus on context-aware anomaly detection and system monitoring. I translate complex models into practical, reliable solutions that work in real-world environments.
Are you looking to apply AI in a clear and effective way in your operations? I would be happy to discuss how to move forward.
Expertise
- Forecasting and time series analysis
- Context-aware anomaly detection
- System and asset monitoring
- Interpretable AI and model transparency
- Transfer learning and model generalisation
Work experience
After completing a master’s and a PhD in applied mathematics at Ghent University, I built expertise in data analysis, forecasting, optimisation and artificial intelligence across different sectors.
Since 2022, I have been working at Sirris, contributing to data-driven innovation projects in industrial and energy contexts.
Studies
- PhD in Applied Mathematics – Ghent University (2007)
- Master in Applied Mathematics – Ghent University (2003)
Fun fact
As a mother of three daughters, I find my balance in endurance sports, with a particular passion for long-distance running and triathlon.