Daniel Schlör

Dr. Daniel Schlör is a researcher at the Chair of Data Science (Informatics X) at the University of Würzburg, with additional affiliations to the CLiGS (Computational Literary Genre Stylistics) research group in Digital Humanities. His work focuses on machine learning for cybersecurity, fraud detection, and explainable AI, with recent projects exploring synthetic data generation, knowledge graph integration, and deep learning for imbalanced datasets.

Research interests include

• Explainable AI (XAI) for anomaly detection
• Deep learning architectures for domain-specific relationships
• Multi-agent simulations for fraud scenario modeling
• Computational stylistics in digital humanities

Article trends show expertise in

• Developing novel neural units (e.g., ModeConv) for structural anomaly differentiation
• Advancing XAI methods with generative inpainting techniques
• Creating open ERP datasets for occupational fraud research
• Applying graph neural networks to water distribution leakage detection

Labs & collaborations include the Data Science Chair’s AI Institute at Hubland Nord campus and CLiGS research group for computational literary analysis.