Martin Briesch (Dr. rer. pol.) is currently a postdoctoral researcher at the chair and conducts research on topics related to machine and evolutionary learning. He successfully completed his doctorate in 2026 with the title “Selected Topics on Machine and Evolutionary Learning” and has been employed as an academic staff member at the chair of Prof. Dr. Franz Rothlauf since 2020. During his doctorate, he also spent 3 months as a visiting scholar at Imperial College London with Prof. Dr. Antoine Cully. Previously, he studied Economics (B.Sc.) from 2014 to 2017 and Management (M.Sc.) from 2017 to 2020 at Johannes Gutenberg University Mainz.
My research units focus on the application and methodological development of approaches from Machine and Evolutionary Learning. In particular, I focus on Large Language Models (LLMs) and Genetic Programming (GP).
2026
Geiger, A., Briesch, M., Sobania, D., and Rothlauf, F. (2026). ROIDS: Robust Outlier-Aware Informed Down-Sampling.
Briesch, M. (2026). On the Effects of Down-Sampling for Tournament and Lexicase Selection in Program Synthesis. In L. Manzoni, S. Cussat-Blanc, and Q. Chen (eds.), Genetic Programming (pp. 3-18). Cham:Springer Nature Switzerland.
2025
Sobania, D., Petke, J., Briesch, M., Rothlauf, F. (2025). A Comparison of Large Language Models and Genetic Programming for Program Synthesis. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 29(4), 1434-1448. DOI Author/Publisher URL
Geiger, A., Briesch, M., Sobania, D., Rothlauf, F. (2025). Was Tournament Selection All We Ever Needed? A Critical Reflection on Lexicase Selection. In B. Xue, L. Manzoni, and I. Bakurov (eds.), EuroGP (Vols. 15609, pp. 207-223). Springer. Author/Publisher URL
Schaeffer, M., Sobania, D., Briesch, M., et al. (2025). Which kind of experts in which loops? Redefining the relationship between translators, data, and models. 11th Congress of the European Society for Translation Studies (EST), Leeds, United Kingdom, 30 June-3 July 2025.
Sobania, D., Briesch, M., Rothlauf, F. (2025). ImageBreeder: Guiding Diffusion Models with Evolutionary Computation. PROCEEDINGS OF THE 2025 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, GECCO 2025, 463-471. DOI Author/Publisher URL
Zoeten, M. C. de, Hauck, M., Briesch, M., et al. (2025). Let Me Entertain You: On the Bias of Editorial and Algorithmic Recommendations in Public Service Media. In I. Lukovic, S. Bjeladinovic, B. Delibasic, et al. (eds.), ISD. University of Gdańsk, University of Belgrade, Association for Information Systems. Author/Publisher URL
2024
Boldi, R., Briesch, M., Sobania, D., et al. (2024). Informed Down-Sampled Lexicase Selection: Identifying Productive Training Cases for Efficient Problem Solving. EVOLUTIONARY COMPUTATION, 32(4), 307-337. DOI Author/Publisher URL
Boldi, R., Bao, A., Briesch, M., et al. (2024). A Comprehensive Analysis of Down-sampling for Genetic Programming-based Program Synthesis. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 487-490. DOI
Boldi, R., Bao, A., Briesch, M., et al. (2024). Untangling the effects of down-sampling and selection in genetic programming. Artificial Life Conference Proceedings 36, 2024, 88-88.
Briesch, M., Boldi, R., Sobania, D., et al. (2024). Improving Lexicase Selection with Informed Down -Sampling. PROCEEDINGS OF THE 2024 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2024 COMPANION, 25-26. DOI Author/Publisher URL
Sobania, D., Briesch, M., Rothlauf, F. (2024). ComfyGI: Automatic Improvement of Image Generation Workflows. CoRR, abs/2411.14193.
2023
Briesch, M., Sobania, D., Rothlauf, F. (2023). Large Language Models Suffer From Their Own Output: An Analysis of the Self-Consuming Training Loop. Author/Publisher URL
Kuhl, E., Zang, C., Esper, J., et al. (2023). Using machine learning on tree-ring data to determine the geographical provenance of historical construction timbers. ECOSPHERE, 14(3). DOI Author/Publisher URL
Boldi, R., Bao, A., Briesch, M., et al. (2023). The Problem Solving Benefits of Down-sampling Vary by Selection Scheme. PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANION, 527-530. DOI Author/Publisher URL
Briesch, M., Sobania, D., Rothlauf, F. (2023). On the Trade-Off between Population Size and Number of Generations in GP for Program Synthesis. PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANION, 535-538. DOI Author/Publisher URL
Huschens, M., Briesch, M., Sobania, D., Rothlauf, F. (2023). Do you trust ChatGPT?–perceived credibility of human and AI-generated content. arXiv preprint arXiv:2309.02524.
Sobania, D., Briesch, M., Hanna, C., Petke, J. (2023). An Analysis of the Automatic Bug Fixing Performance of ChatGPT. 2023 IEEE/ACM INTERNATIONAL WORKSHOP ON AUTOMATED PROGRAM REPAIR, APR, 23-30. DOI Author/Publisher URL
Sobania, D., Briesch, M., Röchner, P., Rothlauf, F. (2023). MTGP: Combining metamorphic testing and genetic programming. European Conference on Genetic Programming (Part of EvoStar), 324-338.
2022
Briesch, M., Sobania, D., and Rothlauf, F. (2022). The Randomness of Input Data Spaces is an A Priori Predictor for Generalization (Vols. 13404, pp. 17-30). DOI Author/Publisher URL
Sobania, D., Briesch, M., and Rothlauf, F. (2022). Choose Your Programming Copilot A Comparison of the Program Synthesis Performance of GitHub Copilot and Genetic Programming. PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO’22), 1019-1027. DOI Author/Publisher URL
Sobania, D., Briesch, M., Wittenberg, D., and Rothlauf, F. (2022). Analyzing Optimized Constants in Genetic Programming on a Real-World Regression Problem. PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2022, 606-607. DOI Author/Publisher URL
I am currently supervising the following subjects:
- Summer semester 2026: Data Science and Machine Learning: Introduction and Application (further information)
I am also happy to supervise master’s theses related to my research fields. Please contact me directly by email with your initial topic proposals.
