Transient dynamic analysis: Performance evaluation of tactile measurement
G. Reschke, A. Brosius, in: Materials Research Proceedings, Materials Research Forum LLC, 2025, pp. 293–300.

Zeit für Arbeitszufriedenheit? Eine quantitativ-empirische Studie zur Bedeutung fester Kooperationszeiten für die Arbeitszufriedenheit von Lehrkräften in inklusiven Schulen
V. Wohnhas, P. Neumann, B. Lütje-Klose, QfI - Qualifizierung für Inklusion. Online-Zeitschrift zur Forschung über Aus-, Fort- und Weiterbildung pädagogischer Fachkräfte 6 (2025).

Mechanical joinability of microstructurally graded structural components manufactured from hypoeutectic aluminium casting alloys
M. Neuser, M.C. Schlichter, K.-P. Hoyer, M. Bobbert, G. Meschut, M. Schaper, 44th Conference of the International Deep Drawing Research Group (IDDRG 2025) 408 (2025).

Mechanical properties and joinability of the near-eutectic aluminium casting alloy AlSi12
M. Neuser, P.K. Holtkamp, K.-P. Hoyer, F. Kappe, S. Yildiz, M. Bobbert, G. Meschut, M. Schaper, The Journal of Materials: Design and Applications, Part L (2025).

Competency Profiles of PCK Using Unsupervised Learning: What Implications for the Structures of pPCK Emerge From Non-Hierarchical Analyses?
J. Zeller, J. Riese, Journal of Research in Science Teaching (2025).

Analysis of the binding mechanisms depending on versatile process variants of self-piercing riveting
S. Lüder, P.K. Holtkamp, S. Wituschek, M. Bobbert, G. Meschut, M. Lechner, H.C. Schmale, in: G. Meschut, M. Bobbert, J. Duflou, L. Fratini, H. Hagenah, P.A.F. Martins, M. Merklein, F. Micari (Eds.), Materials Research Proceedings, Materials Research Forum LLC, Millersville, 2025, pp. 101–108.

Bridging the gap between data-driven and theory-driven modelling – leveraging causal machine learning for integrative modelling of dynamical systems
D.R. Zapata Gonzalez, M. Meyer, O. Müller, in: 2025.

The power of combined modalities in interactive robot learning
H. Beierling, R. Beierling, A.-L. Vollmer, Frontiers in Robotics and AI 12 (2025).

Human-Interactive Robot Learning: Definition, Challenges, and Recommendations
K. Baraka, I. Idrees, T.K. Faulkner, E. Biyik, S. Booth, M. Chetouani, D.H. Grollman, A. Saran, E. Senft, S. Tulli, A.-L. Vollmer, A. Andriella, H. Beierling, T. Horter, J. Kober, I. Sheidlower, M.E. Taylor, S. van Waveren, X. Xiao, Transactions on Human-Robot Interaction (n.d.).

Efficient failure information propagation under complex stress states in fiber reinforced polymers: From micro- to meso-scale using machine learning
J. Gerritzen, A. Hornig, M. Gude, in: G. Meschut, M. Bobbert, J. Duflou, L. Fratini, H. Hagenah, P. Martins, M. Merklein, F. Micari (Eds.), Sheet Metal 2025, Materials Research Forum LLC, Materials Research Foundations, 2025, pp. 260–267.

Tree-Based OWL Class Expression Learner over Large Graphs
C. Demir, M. Yekini, M. Röder, Y. Mahmood, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.

Parameter Averaging in Link Prediction
R. Sapkota, C. Demir, A. Sharma, A.-C. Ngonga Ngomo, in: Proceedings of the Thirteenth International Conference on Knowledge Capture(K-CAP 2025), ACM, Dayton, OH, USA, 2025.

Fostering self-regulated entrepreneurial learning in entrepreneurship education
M. Fahrbach, T. Jenert, A. Fust, N. Bellwald, C. Winkler, in: Annals of Entrepreneurship Education and Pedagogy - 2025, Edward Elgar Publishing, 2025, pp. 249–265.

HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores
W. Kirchgässner, N. Förster, T. Piepenbrock, O. Schweins, O. Wallscheid, IEEE Transactions on Power Electronics 40 (2025) 3326–3335.

LOCAL DEFORMATION AND FAILURE OF COMPOSITES DURING SELF-PIERCING RIVETING: A CT BASED MICROSTRUCTURE INVESTIGATION
A. Dargel, B. Gröger, M.C. Schlichter, J. Gerritzen, D. Köhler, G. Meschut, M. Gude, R. Kupfer, in: J.F.S. Gomes, S.A. Meguid (Eds.), Proceedings of the 8th International Conference on Integrity-Reliability-Failure (I), FEUP, Porto, 2025.

Diagnostics of Piezoelectric Bending Actuators Subjected to Varying Operating Conditions
O.K. Aimiyekagbon, A. Bender, T. Hemsel, W. Sextro, Electronics 13 (2024).

Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines
H. Harder, S. Peitz, (n.d.).

Fähigkeitsprofile im Physikdidaktischen Wissen mithilfe von Machine Learning
J. Zeller, J. Riese, in: H. van Vorst (Ed.), Frühe naturwissenschaftliche Bildung, Tagungsband der GDCP Jahrestagung 2023, Gesellschaft für Didaktik der Chemie und Physik, Hamburg, 2024, pp. 122–125.

Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification
C. Offen, (n.d.).

Assessment des physikdidaktischen Wissens mithilfe von Machine Learning
J. Zeller, J. Riese, in: Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024, n.d.