CV

General Information

Name: Lukas Paul Achatius Galke Poech

Address: Campusvej 55, 5230 Odense, Denmark

Office: Ø12-509b-2

Experience

Current position (since 2026): Associate Professor, University of Southern Denmark, Faculty of Science, Department of Mathematics and Computer Science, Section for Data Science and Statistics, Centre for Machine Learning

2024-2026: Assistant Professor, University of Southern Denmark, Department of Mathematics and Computer Science

2022-2024: Postdoctoral Researcher, Max Planck Institute for Psycholinguistics

2017-2022: Doctoral Researcher, Kiel University & ZBW

Education

2022: PhD in Computer Science, Kiel University, Germany

2017: M.Sc. in Computer Science, Kiel University, Germany

2013: BSc in Computer Science, Kiel University, Germany

Grants and Major Projects

MIST: Scalable Mechanistic Interpretability for Safe and Trustworthy LLM Agents (2026–2031, Novo Nordisk Foundation) Role: Principal investigator.

Danish Foundation Models (2025–2028) Consortium: University of Southern Denmark, Aarhus University, Alexandra Institute, Copenhagen University. Role: Work package leader

Selected publications

• Stine Lyngsø Beltoft, William Brach, Federico Torrielli, Jacob Nielsen, Annemette Brok Pirchert, Filippo Tonini, Peter Schneider-Kamp, and Lukas Galke Poech (2026). Emergent Languages in Agent Populations: From Token Efficiency to Oversight Evasion. AIES.
• Niklas Mellgren, Peter Schneider-Kamp, Lukas Galke Poech (2026). Training Language Models to Use Prolog as a Tool. ACL Findings.
• Danial Namazifard and Lukas Galke (2025). Isolating Culture Neurons in Multilingual Large Language Models. AACL-IJCNLP Findings.
• Richard Šléher, William Brach, Tibor Sloboda, Kristián Košťál, and Lukas Galke (2025). Guarded Query Routing for Large Language Models. ECAI.
• Lukas Galke, Yoav Ram, and Limor Raviv (2024) Deep neural networks and humans both benefit from compositional language structure. Nature Communications 15:10816.

Selected invited talks

• Cooperation, Culture, and Coordination in Neural Ecosystems. Lamarr NLP Colloquium, Lamarr Institute for Artificial Intelligence and Machine Learning, 2026, Feb 11, Bonn, Germany.
• Evaluating Large and Multilingual Language Models through Citizen Science. AI, Citizen Science, and MedTech – An Exploration, 2025, May 13, SDU, Odense, Denmark.
• Emergent communication and learning pressures in language models. Workshop on Using Artificial Neural Networks for Studying Human Language Learning and Processing, 2024, June 10, University of Amsterdam.
• What makes a language easy to deep-learn? Computational Linguistics Seminar, 2023, May 16, University of Amsterdam, Netherlands.

Teaching experience

• Natural Language Processing (2025, 2026)
• Computer Vision (co-teacher 2025, 2026)
• Advanced Machine Learning (2025, 2026)
• Deep Learning (main teacher 2024; responsible teacher 2025, 2026)

Academic service

• Program Chair: ICNLSP 2025
• Program Committee: ACL, EMNLP, NeurIPS, ICLR, ICML, AAAI, ECAI, …
• Journal Reviewer: Nature Human Behavior, Nature Communications, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, Neural Networks, Pattern Recognition, Journal of Artificial Intelligence Research (JAIR), …