معرفی
Professor Stephan Seifert leads research at the University of Hamburg's Department of Chemistry, focusing on chemometrics and bioinformatic methods for food profiling and manuscript analysis. His group develops analytical approaches using vibrational spectroscopy, machine learning, and data fusion techniques.
Research spans:
- Chemometric method development (random forests, variable selection)
- Spectroscopic analysis (FTIR, Raman, NMR)
- Food authentication and quality control
- Manuscript material characterization
Recent publications demonstrate increasing use of machine learning for metabolomics data interpretation and multi-technique data fusion. Research integrates analytical chemistry with computational approaches to solve problems in food science and cultural heritage.
Current projects include the Cluster of Excellence 'Understanding Written Artefacts' and Palm-Leaf Manuscript Profiling Initiative. Leads the Seifert AG research group at the Institute of Food Chemistry.
