Deutsch Intern
    Data Science Chair

    Dr. Daniel Schlör

    Chair of Data Science (Informatik X)
    University of Würzburg
    Campus Hubland Nord
    Emil-Fischer-Straße 50
    97074 Würzburg
    Germany

    Email: daniel.schloer[at]informatik.uni-wuerzburg.de

    Phone: (+49 931)  31 - 84564

    Office: Room 50.03.017 (Institutsgebäude Künstliche Intelligenz)

    I am currently working as an interim professor at the University of Cologne and am therefore not regularly available in my office at JMU. Please make an appointment by email.

    Projects and Research Interests

    My research sits at the intersection of Data and Knowledge Engineering and Machine Learning, with a strong applied focus on Cyber security. I currently lead the Machine Learning for Cyber Security research group and two funded projects, DEMAnD-LM and BRACE-LLM.

    My research is organized along three interconnected themes:

    • Data Engineering and Knowledge Graphs: continual integration of KGs into language models (CapsKG, PreAdapter (ISWC23,24), CGKGC (ESWC26)), data pipelines for heterogeneous sources, synthetic data generation and benchmarking
    • AI/ML for Cyber security: formalizing security knowledge for LLM-based agents, explainable AI, and robustness of ML-based security systems but also cyber security in a broader sense: offensive and defensive perspectives, industry collaborations in penetration testing, and practical / human-in-the-loop perspectives
    • Security Analytics and Anomaly Detection: intrusion and malware detection on network flows and audit logs, red- and blue-team agents in cyber ranges for realistic data generation and evaluation

    Teaching

    Publications

    2026[ to top ]
    • Schlör, D., Bohn, M., Wolf, M., Bergner, K., Goldschmied, C., and Hotho, A. (2026) “Towards Knowledge Graph-Grounded Evaluation of Agentic LLMs on Cybersecurity Capture-the-Flag Challenges”, 15th edition of the Language Resources and Evaluation Conference, KG & LLM @ LREC.
    • Usman Butt, M., Hotho, A., and Schlör, D. (2026) “Evaluating Tabular Representation Learning for Network Intrusion Detection”, IEEE CSR - IEEE International Conference on Cyber Security and Resilience.
    • Wolf, M., Landes, D., Hotho, A., and Schlör, D. (2026) “Rethinking Synthetic Oversampling for Intrusion Detection: When Similarity Hurts Performance”, CISIS 2026 - 19th International Conference on Computational Intelligence in Security for Information Systems.
    • Omeliyanenko, J., Hotho, A., and Schlör, D. (2026) “Parameter Efficient Continual Automated Knowledge Graph Completion”, ESWC 2026 - 23rd European Semantic Web Conference.
    2025[ to top ]
    • Fischer, E., Zehe, A., Hotho, A., and Schlör, D. (2025) “Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction”, ACM Trans. Recomm. Syst., available: https://doi.org/10.1145/3721298.
    • Röchner, P., Klüttermann, S., Rothlauf, F., and Schlör, D. (2025) “We Need to Rethink Benchmarking in Anomaly Detection”.
    2024[ to top ]
    • Fischer, E., Zehe, A., Hotho, A., and Schlör, D. (2024) “Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction”, available: https://arxiv.org/abs/2408.15953.
    • Tritscher, J., Lissmann, P., Wolf, M., Krause, A., Hotho, A., and Schlör, D. (2024) “Generative Inpainting for Shapley-Value-Based Anomaly Explanation”, The World Conference on eXplainable Artificial Intelligence (xAI 2024).
    • Hesselbach, R., Calvo Tello, J., Henny-Krahmer, U., Schöch, C., and Schlör, D. (2024) “Digital Stylistics in Romance Studies and Beyond”.
    • Tritscher, J., Wolf, M., Krause, A., Hotho, A., and Schlör, D. (2024) “Data Generation for Explainable Occupational Fraud Detection”, 47th German Conference on Artificial Intelligence (KI 2024) - to appear.
    • Omeliyanenko, J., Hotho, A., and Schlör, D. (2024) “PreAdapter: Pre-training Language Models on Knowledge Graphs”, International Semantic Web Conference ISWC 2024, to appear.
    • Schaller, M., Schl{{ö}}r, D., and Hotho, A. (2024) “ModeConv: {A} Novel Convolution for Distinguishing Anomalous and Normal Structural Behavior”, CoRR, abs/2407.00140, available: https://doi.org/10.48550/ARXIV.2407.00140.
    • Wolf, M., Tritscher, J., Landes, D., Hotho, A., and Schlör, D. (2024) “Benchmarking of synthetic network data: Reviewing challenges and approaches.”, Computers and Security, 145, 103993, available: http://dblp.uni-trier.de/db/journals/compsec/compsec145.html#WolfTLHS24.
    • Wolf, M., Landes, D., Hotho, A., and Schlör, D. (2024) “Systematic Evaluation of Synthetic Data Augmentation for Multi-class NetFlow Traffic.”, CoRR, abs/2408.16034, available: http://dblp.uni-trier.de/db/journals/corr/corr2408.html#abs-2408-16034.
    • Schl{ö}r, D. and Hotho, A. (2024) “Verantwortungsvolle Empfehlungssysteme f{ü}r die medizinische Diagnostik”, Edition Moderne Postmoderne, 101.
    2023[ to top ]
    • Omeliyanenko, J., Zehe, A., Hotho, A., and Schlör, D. (2023) “CapsKG: Enabling Continual Knowledge Integration in Language Models for Automatic Knowledge Graph Completion”, International Semantic Web Conference ISWC 2023, to appear.
    • Schlör, D., Pfister, J., and Hotho, A. (2023) “Optimizing Medical Service Request Processes through Language Modeling and Semantic Search”, in 2023 the 7th International Conference on Medical and Health Informatics (ICMHI), ICMHI 2023, Kyoto, Japan: Association for Computing Machinery, 136–141, available: https://doi.org/10.1145/3608298.3608324.
    • Fischer, E., Schlör, D., Zehe, A., and Hotho, A. (2023) “Enhancing Sequential Next-Item Prediction through Modelling Non-Item Pages”.
    • Tritscher, J., Wolf, M., Hotho, A., and Schlör, D. (2023) “Evaluating feature relevance XAI in network intrusion detection”, The World Conference on eXplainable Artificial Intelligence (xAI 2023) - to appear.
    • Tritscher, J., Roos, A., Schlör, D., Hotho, A., and Krause, A. (2023) “Occupational Fraud Detection through Agent-based Data Generation”, The 8th Workshop on MIning DAta for financial applicationS MIDAS 2023 - to appear.
    • Schaller, M., Steininger, M., Dulny, A., Schlör, D., and Hotho, A. (2023) “Liquor-HGNN: A heterogeneous graph neural network for leakage detection in water distribution networks”, LWDA’23: Lernen, Wissen, Daten, Analysen. October 09--11, 2023, Marburg, Germany.
    2022[ to top ]
    • Tritscher, J., Gwinner, F., Schlör, D., Krause, A., and Hotho, A. (2022) “Open ERP System Data For Occupational Fraud Detection”, available: http://arxiv.org/abs/2206.04460.
    • Schlör, D. and Hotho, A. (2022) “Towards Responsible Medical Diagnostics Recommendation Systems”, CoRR, abs/2209.03760, available: https://doi.org/10.48550/arXiv.2209.03760.
    • Schlör, D. (2022) Detecting Anomalies in Transaction Data, PhD dissertation, available: https://doi.org/10.25972/OPUS-29856.
    • Schlör, D. and Hotho, A. (2022) “Towards Responsible Medical Diagnostics Recommendation Systems”, available: http://arxiv.org/abs/2209.03760.
    2021[ to top ]
    • Tritscher, J., Krause, A., Schlör, D., Gwinner, F., Von Mammen, S., and Hotho, A. (2021) “A financial game with opportunities for fraud”, in 2021 IEEE Conference on Games (CoG), 1–5, available: https://doi.org/10.1109/CoG52621.2021.9619070.
    • Ring, M., Schlör, D., Wunderlich, S., Landes, D., and Hotho, A. (2021) “Malware detection on windows audit logs using LSTMs”, Computers & Security, 109, 102389, available: https://doi.org/https://doi.org/10.1016/j.cose.2021.102389.
    2020[ to top ]
    • Tritscher, J., Ring, M., Schlör, D., Hettinger, L., and Hotho, A. (2020) “Evaluation of Post-hoc XAI Approaches Through Synthetic Tabular Data.”, in Helic, D., Leitner, G., Stettinger, M., Felfernig, A. and Ras, Z.W., eds., ISMIS, Lecture Notes in Computer Science, Springer, 422–430, available: http://dblp.uni-trier.de/db/conf/ismis/ismis2020.html#TritscherRSHH20.
    • Schlör, D., Ring, M., Krause, A., and Hotho, A. (2020) Financial Fraud Detection With Improved Neural Arithmetic Logic Units.
    • Schlör, D., Ring, M., and Hotho, A. (2020) “iNALU: Improved Neural Arithmetic Logic Unit”, Frontiers in Artificial Intelligence, 3, 71, available: https://doi.org/10.3389/frai.2020.00071.
    • Schl{ö}r, D., Zehe, A., Kobs, K., Veseli, B., Westermeier, F., Br{ü}bach, L., Roth, D., Latoschik, M.E., and Hotho, A. (2020) “Improving Sentiment Analysis with Biofeedback Data”, in Proceedings of LREC2020 Workshop ``People in Language, Vision and the mind’’ (ONION2020), Marseille, France: European Language Resources Association (ELRA), 28–33, available: https://www.aclweb.org/anthology/2020.onion-1.5.
    2019[ to top ]
    • Schl{ö}r, D., Sch{ö}ch, C., and Hotho, A. (2019) “Classification of text-types in german novels”, in Digital Humanities 2019: Conference Abstracts, available: https://doi.org/https://doi.org/10.34894/OMLKRN.
    • Ring, M., Schlör, D., Landes, D., and Hotho, A. (2019) “Flow-based network traffic generation using Generative Adversarial Networks.”, Comput. Secur., 82, 156–172, available: http://dblp.uni-trier.de/db/journals/compsec/compsec82.html#RingSLH19.
    2018[ to top ]
    • Schöch, C., Schlör, D., Zehe, A., Gebhard, H., Becker, M., and Hotho, A. (2018) “Burrows’ Zeta: Exploring and Evaluating Variants and Parameters”, in DH, 274–277, available: http://dblp.uni-trier.de/db/conf/dihu/dh2018.html#SchochSZG0H18.
    • Zehe, A., Schlör, D., Henny-Krahmer, U., Becker, M., and Hotho, A. (2018) “A White-Box Model for Detecting Author Nationality by Linguistic Differences in Spanish Novels”, in DH, ADHO.
    2017[ to top ]
    • Tello, J.C., Schlör, D., Henny-Krahmer, U., and Schöch, C. (2017) “Neutralising the Authorial Signal in Delta by Penalization: Stylometric Clustering of Genre in Spanish Novels.”, in Lewis, R., Raynor, C., Forest, D., Sinatra, M. and Sinclair, S., eds., DH, Alliance of Digital Humanities Organizations (ADHO), available: http://dblp.uni-trier.de/db/conf/dihu/dh2017.html#TelloSHS17.
    2016[ to top ]
    • Sch{ö}ch, C., Schl{ö}r, D., Popp, S., Brunner, A., Henny, U., and Tello, J.C. (2016) “Straight Talk! Automatic Recognition of Direct Speech in Nineteenth-Century French Novels.”, in DH, 346–353.
    • Niebler, T., Schlör, D., Becker, M., and Hotho, A. (2016) “Extracting Semantics from Unconstrained Navigation on Wikipedia”, KI -- Künstliche Intelligenz, 30(2), 163–168.