Puiseau, C., Ercan, F., Peters, J., Brune, M., Tercan, H., Prinz, C., Meisen, T., & Kuhlenkötter, B. (2026). "A literature review on deep reinforcement learning for machine scheduling problems" , Journal of Manufacturing Systems , 85 , 96—126.

Voets, J., Tercan, H., Meisen, T., & Esen, C. (2026). "A Systematic Review and Taxonomy of Machine Learning Methods for Process Optimization and Control in Laser Welding" , Applied Sciences , 16 (3), 1568.

Varici, M. D., Tercan, H., & Meisen, T. (2026). Bridging the Synchrony Gap: A Deterministic GSMDP Approach for Integrating Deep Reinforcement Learning with Commercial Discrete Event Simulators . Offenburg : publish-Ing.

Chandorkar, A., Krink, K., Maulenbay, Y., Tercan, H., & Meisen, T. (2026). Comprehensive Robustness Analysis of LiDAR-based 3D Object Detection in Autonomous Driving.

Voets, J., Tercan, H., Meisen, T., & Baum, S. (2026). ConTex: Reformulating Counterfactual Generation For Time Series Forecasting.

Hahn, Y., Königsfeld, A., Tercan, H., & Meisen, T. (2026). EXCODER: EXplainable Classification Of DiscretE time series Representations.

Hubbertz, M., Han, Q., & Meisen, T. (2026). Failure Modes for Deep Learning-Based Online Mapping: How to Measure and Address Them.

Busch, D., Bohn, C., Kurbiel, T., Friedrichs, K., Meyes, R., & Meisen, T. (2026). Faster Training, Fewer Labels: Self-Supervised Pretraining for Fine-Grained BEV Segmentation.

Yadav, H., & Meisen, T. (2026). Goal-Oriented Reactive Simulation for Closed-Loop Trajectory Prediction.

Stillger, F., Hahn, L., Hasecke, F., & Meisen, T. (2026). InCaRPose: In-Cabin Relative Camera Pose Estimation Model and Dataset.

Weiss, M., Mrzljak, K., Schmid, M., Erbach, G., Brierley, N., & Meisen, T. (2026). "Material-resolving computed tomography of lithium-ion batteries using deep learning" , NDT & E International , 158 (1), 103565.

Hadwiger, S., Kube, D., & Meisen, T. (2026). "Partial observability in vision-based forklift navigation with compressed visual information" , International Journal of Intelligent Robotics and Applications .

Yadav, H., Bohn, C., & Meisen, T. (2026). Rectify, Don't Regret: Avoiding Pitfalls of Differentiable Simulation in Trajectory Prediction.

Kube, D., Hadwiger, S., & Meisen, T. (2026). Robotic Foundation Models for Industrial Control: A Comprehensive Survey and Readiness Assessment Framework.

Stillger, F., Hamscher, B., Hahn, L., Mütze, A., Meisen, T., & Maag, K. (2026). Texture-Shape Bias Balancing for Robust Synthetic-to-Real Semantic Segmentation in Automotive NIR Imagery.