معرفی
Dr. Hussein Mohammed is a Researcher and Head of the Visual Manuscript Analysis Lab at the University of Hamburg's Centre for the Study of Manuscript Cultures (CSMC). He leads the Cluster of Excellence 'Understanding Written Artefacts' (UWA) and the Visual Manuscript Analysis (VMA) Lab. His roles include Principal Investigator and Project Lead for initiatives like 'Similarity Measurement of Visual Patterns in Written Artefacts' and 'Pattern Recognition in 2D Data from Digitized Images.'
He holds a doctoral degree (Dr. rer. nat.) in computer science from Hamburg University, focusing on computational analysis of handwriting styles. His research emphasizes pattern recognition, machine learning, and computer vision applied to historical manuscripts. Key projects include developing tools like the Pattern Analysis Software Tools (PAST), AFAT, and HAT to analyze visual features and aid cultural heritage preservation.
His work bridges computer science and humanities, with contributions to palimpsest deciphering via generative AI, artifact feature analysis, and multimodal data integration. Notable awards include the Erasmus Mundus Scholarship (2012). He also contributes to academic outreach through lectures on computational paleography and manuscript digitization.
