Modeling and Simulation Group · Neuro-Mechanistic Modeling
Saarland University & DFKI

Computational Models for Complex Systems

Welcome to the joint website of the Saarland University chair Modeling and Simulation and the DFKI research department Neuro-Mechanistic Modeling. We develop computational methods for the simulation and analysis of complex real-world systems. At the core of our research is the combination of established knowledge in the form of mechanistic models with data-driven AI methods. These hybrid approaches enable precise and interpretable results even with moderate amounts of data, thus opening up new application areas for artificial intelligence.

Latest News

Latest Publications

Assay-Based Machine Learning: Rethinking Evaluation in Drug Discovery

Joschka Groß, Michael Backenköhler and Andrea Volkamer

2026 — Digital Discovery

@article{grossAssayBasedMachineLearningRethinking2026,
 author = {Groß, Joschka and Backenköhler, Michael and Volkamer, Andrea},
 doi = {10.1039/D6DD00472E},
 eprint = {https://pubs.rsc.org/dd/article-pdf/doi/10.1039/D6DD00472E/15052126/d6dd00472e.pdf},
 issn = {2635-098X},
 journal = {Digital Discovery},
 month = {11},
 title = {Assay-Based Machine Learning: Rethinking Evaluation in Drug Discovery},
 url = {https://doi.org/10.1039/D6DD00472E},
 year = {2026}
}
DOI URL

How PC-based Methods Err: Towards Better Reporting of Assumption Violations and Small Sample Errors

Sofia Faltenbacher, Jonas Wahl, Rebecca Jean Herman and Jakob Runge

2026 — Proceedings of the 42nd Conference on Uncertainty in Artificial Intelligence

@inproceedings{faltenbacherHowPCBasedMethodsErr2026,
 author = {Faltenbacher, Sofia and Wahl, Jonas and Herman, Rebecca Jean and Runge, Jakob},
 booktitle = {Proceedings of the 42nd Conference on Uncertainty in Artificial Intelligence},
 editor = {Perković, Emilija and Malinsky, Daniel},
 month = {Aug},
 pages = {1498--1519},
 pdf = {https://raw.githubusercontent.com/mlresearch/v337/main/assets/faltenbacher26a/faltenbacher26a.pdf},
 publisher = {PMLR},
 series = {Proceedings of Machine Learning Research},
 title = {How PC-based Methods Err: Towards Better Reporting of Assumption Violations and Small Sample Errors},
 url = {https://proceedings.mlr.press/v337/faltenbacher26a.html},
 volume = {337},
 year = {2026}
}
URL

Per-Domain Generalizing Policies: On Learning Efficient and Robust Q-Value Functions

Nicola J. Müller, Moritz Oster, Isabel Valera, Jörg Hoffmann and Timo P. Gros

2026 — Proceedings of the Thirty-Sixth International Conference on Automated Planning and Scheduling. International Conference on Automated Planning and Scheduling (ICAPS-2026), June 27 - July 2, Dublin, Ireland

@inproceedings{mullerPerDomainGeneralizingPoliciesOn2026,
 author = {Müller, Nicola J. and Oster, Moritz and Valera, Isabel and Hoffmann, Jörg and Gros, Timo P.},
 booktitle = {Proceedings of the Thirty-Sixth International Conference on Automated Planning and Scheduling. International Conference on Automated Planning and Scheduling (ICAPS-2026), June 27 - July 2, Dublin, Ireland},
 doi = {10.1609/icaps.v36i1.42889},
 isbn = {ISSN 2334-0843},
 month = {6},
 number = {1},
 pages = {703-707},
 publisher = {AAAI Press},
 title = {Per-Domain Generalizing Policies: On Learning Efficient and Robust Q-Value Functions},
 url = {https://ojs.aaai.org/index.php/ICAPS/article/view/42889},
 volume = {36},
 year = {2026}
}
DOI URL

Evaluation beyond goodness of fit: Quantifying biophysical alignment of AI models for kinase-centric drug discovery

Joschka Groß, Michael Backenköhler, Paula Linh Kramer, Raquel López-Ríos De Castro, Guillermo Pérez-Hernández, Verena Wolf and Andrea Volkamer

2026 — Artificial Intelligence in the Life Sciences (AILSCI)

@article{grossEvaluationBeyondGoodnessOf2026,
 author = {Joschka Groß and Michael Backenköhler and Paula Linh Kramer and Raquel López-Ríos De Castro and Guillermo Pérez-Hernández and Verena Wolf and Andrea Volkamer},
 doi = {10.1016/j.ailsci.2026.100169},
 journal = {Artificial Intelligence in the Life Sciences (AILSCI)},
 month = {6},
 number = {article 100169},
 pages = {1-17},
 publisher = {Elsevier},
 title = {Evaluation beyond goodness of fit: Quantifying biophysical alignment of AI models for kinase-centric drug discovery},
 url = {https://www.sciencedirect.com/science/article/pii/S2667318526000176?via%3Dihub},
 volume = {9},
 year = {2026}
}
DOI URL

Chaotic and complex dynamics expose the limits of counterfactual reasoning

Yahya Aalaila, Gerrit Großmann, Sumantrak Mukherjee, Jonas Wahl and Sebastian Vollmer

2026 — Scientific Reports (Sci Rep)

@article{aalailaChaoticAndComplexDynamics2026,
 author = {Yahya Aalaila and Gerrit Großmann and Sumantrak Mukherjee and Jonas Wahl and Sebastian Vollmer},
 doi = {10.1038/s41598-026-52349-2},
 journal = {Scientific Reports (Sci Rep)},
 month = {6},
 number = {1},
 pages = {1-14},
 publisher = {Springer Nature},
 title = {Chaotic and complex dynamics expose the limits of counterfactual reasoning},
 url = {https://www.nature.com/articles/s41598-026-52349-2},
 volume = {16},
 year = {2026}
}
DOI URL