Discrepancy Modeling for Dynamical Systems
F.-M. Dockhorn, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 35. Workshop Computational Intelligence, Karlsruher Institut für Technologie (KIT), 2025.

AI Workflow for Scarce Data: A Modular Approach to Optimise Processes
J. Bültemeier, C.-A. Holst, V. Lohweg, M. Schöne, B. Jaster, M. Kohlhase, in: 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2025, pp. 1–4.

Informed Active Learning with Decision Trees to Balance Exploration and Exploitation
M. Schöne, B. Jaster, J. Bültemeier, M. Kohlhase, in: Institute for Data Science Solutions (Ed.), Kongress KI@HS Zukunft Im Fokus – Posterbeiträge, Hochschule Bielefeld, Bielefeld, 2025, pp. 26–27.

Sensorintegration in Orthesen zur Versorgung des Diabetischen Fußsyndroms: eine technische Betrachtung
V. Katter, C. Huperz, M. Kohlhase, J. Bartsch, I. Özlu, M. Regier, R.I. Amelung, B. Klemme, Orthopädie Technik (2025) 68–73.

Für eine inklusive digitale Zukunft: Ableismus-sensible Chatbots gestalten
F. Bäumer, H. Brandt-Pook, C. Huppert, Y. Sir, A. Stahlkopf, F. Sang, N. Ullrich, 2 (2025).

LLM gesteuerte Planung zur Reduktion des CO2-Fußabdrucks im Tiefbau
A. Matutat, L. Golin, H. Brandt-Pook, in: Gesellschaft für Informatik e.V. (Ed.), INFORMATIK 2025, Bonn, 2025, pp. 1345–1350.

Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES
M. Sangel, E. Bensch, H. Brandt-Pook, T. Röllke, C. Markworth, in: Gesellschaft für Informatik e.V. (Ed.), INFORMATIK 2025, Bonn, 2025, pp. 1363–1371.

Green by Design: Nachhaltiger Tiefbau durch KI
L. Golin, A. Matutat, H. Brandt-Pook, 2 (2025) 18–19.

Eine KI-Reise im Mittelstand
F. Prekwinkel, H. Brandt-Pook, Wirtschaftsinformatik &; Management (2025).

Beyond Q&A: Entwicklung eines agentenbasierten Retrieval-Augmented-Generation-Systems bei der imos AG
R. Bourdick, F. Bäumer, in: Jahrestagung Der Gesellschaft Für Informatik, 2025.

Trust Issues in Active Learning and Their Impact on Real-World Applications
B. Jaster, M. Kohlhase, in: IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), IEEE, 2025, pp. 1–5.

Trust Issues in Active Learning and Their Impact on Real-World Applications
B. Jaster, M. Kohlhase, in: IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), IEEE, 2025, pp. 1–5.

Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit
M. Schöne, B. Jaster, J. Bültemeier, J. Kösters, C.-A. Holst, M. Kohlhase, in: IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), IEEE, 2025, pp. 1–9.

Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit
M. Schöne, B. Jaster, J. Bültemeier, J. Kösters, C.-A. Holst, M. Kohlhase, in: IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), IEEE, 2025, pp. 1–9.

Multimodal Analysis of Modern Phishing Attacks: Towards an Evolving Dataset of Real-World Data
S. Schultenkämper, F. Bäumer, in: The 13th IEEE International Workshop on Semantic Computing for Social Networking: From User Information to Social Knowledge and Ethical AI, 2025.

Enhancing Social Media Summarization with Instruction Tuned Large Language Models and Adaptive Summary Ranking
S. Schultenkämper, V. Vovchenko, F. Bäumer, in: The 13th IEEE International Workshop on Semantic Computing for Social Networking: From User Information to Social Knowledge and Ethical AI, 2025.

A Comparative Analysis of ChatGPT-Generated and Human-Written Use Case Descriptions
E. Aslan Oguz, J. Küster, in: Association for Computing Machinery (Ed.), Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, ACM, New York, NY, USA, 2024, pp. 533–540.

Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme 
V. Katter, B. Jaster, M. Schöne, Schriftenreihe des Institute for Data Science Solutions 2 (2024).

An Application-oriented Review of Standard and Integral Sparse Identification of Nonlinear Dynamics
F.-M. Dockhorn, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings - 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024, KIT Scientific Publishing, 2024, pp. 53–76.

Design decisions for integrating Prescriptive Analytics Use Cases into Smart Factories
J. Weller, N. Migenda, S. von Enzberg, M. Kohlhase, W. Schenck, R. Dumitrescu, Procedia CIRP 128 (2024) 424–429.