Dr. Hassan El Hajj
Dr. Hassan El Hajj
Senior Data Scientist & Research IT Scholar
External Partner | BIFOLD
Senior Data Scientist and a Research IT Scholar at the Max Planck Institute for the History of Science
Hassan El Hajj is a Senior Data Scientist and a Research IT Scholar at the Max Planck Institute for the History of Science. He received an M.A. in Archaeology focusing on network analysis from the American University of Beirut, an M.Sc. in Geographic Information Sciences with a focus on Computer Vision and Remote Sensing from the Technische Universität Berlin, and holds a PhD in Classical Archaeology from the Philipps-Universität Marburg focusing on geospatial analysis. His research centers on the application of Machine Learning for information extraction and insight generation within the humanities and cultural heritage domains.
- Digital Humanities
- Historical and Complex Document Analysis
- Machine Learning for Knowledge Graphs
- Explainable AI
- AI for Cultural Heritage
Hassan El-Hajj, Matteo Valleriani
Prompt me a Dataset: An investigation of text-image prompting for historical image dataset creation using foundation models
Maryam Zamani, Hassan El-Hajj, Malte Vogl, Holger Kantz, Matteo Valleriani
A mathematical model for the process of accumulation of scientific knowledge in the early modern period
Jochen Büttner, Julius Martinetz, Hassan El-Hajj, Matteo Valleriani
CorDeep and the Sacrobosco Dataset: Detection of Visual Elements in Historical Documents
Hassan El-Hajj, Maryam Zamani, Jochen Büttner, Julius Martinetz, Oliver Eberle, Noga Shlomi, Anna Siebold, Grégoire Montavon, Klaus-Robert Müller, Holger Kantz & Matteo Valleriani
An Ever-Expanding Humanities Knowledge Graph: The Sphaera Corpus at the Intersection of Humanities, Data Management, and Machine Learning
Hassan El Hajj, Matteo Valleriani
CIDOC2VEC: Extracting Information from Atomized CIDOC-CRM Humanities Knowledge Graphs
Peter-Haber-Preis for AI in historical sciences
Bachelor student Anika Merklein's award-winning poster uses AI to unveil secrets of early printing.
Detecting Visual Elements in Historical Documents
Historians are increasingly in need of digital tools to process and extract information from electronic copies of historical sources. BIFOLD scientists developed YOLO (You Only Look Once).