Research
Scientific theme.
Our research brings together magnetic resonance, microfluidics, metabolomics, and computational analysis to study complex chemical and biological systems. We are interested in methods that make measurements more informative, more robust, and more accessible in small volume and data rich experimental settings. This page presents the group’s main scientific directions at a high level, while more detailed technical developments remain within publications.
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Microfluidic NMR
We are interested in the integration of nuclear magnetic resonance with controlled small volume environments. By combining NMR with microfluidic platforms, it becomes possible to study chemical and biological systems in ways that are efficient, non destructive, and compatible with dynamic measurements. This area of research supports the development of experimental methods for analysing limited sample volumes, monitoring processes over time, and linking microscale platforms with information rich magnetic resonance measurements.
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Metabolomics
Our work in metabolomics focuses on the measurement and interpretation of complex chemical profiles from biological and model systems. We are particularly interested in quantitative and time resolved analysis, where magnetic resonance can provide insight into metabolic composition and change over time. This research direction connects spectroscopy, analytical methodology, and data interpretation to better understand dynamic biochemical processes in challenging samples.
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AI for Spectral Analysis
We explore machine learning and computational methods that support the analysis of magnetic resonance data. These approaches include tasks such as denoising, signal reconstruction, pattern extraction, and the development of more automated analysis workflows. The overall aim is to improve the reliability and usability of spectral data while creating tools that can assist researchers in extracting meaningful information from complex measurements.