CV

General Information

Name: Lukas Paul Achatius Galke Poech

Address: Campusvej 55, 5230 Odense, Denmark

Office: Ø12-509b-2

Experience

Current position (since 2024): Assistant Professor, University of Southern Denmark (SDU), Department of Mathematics and Computer Science (IMADA), Section for Data Science and Statistics (DSS), Centre for Machine Learning (C4ML)

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, Principal Investigator, Funding for 2 PhD + 1 Postdoc position to develop interpretability methods for understanding and controlling LLM agents.

Sustainable Language Modeling through Quantization-Aware Continual Pre-training (2025) EuroHPC JU AI and Data Intensive Applications, Principal Investigator, 200,000 GPU hours

Danish Foundation Models (2025–2029) Danish Government Initiative, Work Package Co-Lead (Evaluation), co-supervising 5 PhD students

Selected publications

Mogens From, Jacob Nielsen, Lukas Galke, and Peter Schneider-Kamp (2026). DeToNATION: Decoupled Torch Network-Aware Training on Interlinked Online Nodes. AAAI.
Danial Namazifard and Lukas Galke (2025). Isolating Culture Neurons in Multilingual Large Language Models. To appear in: AACL-IJCNLP Findings.
Richard Šléher, William Brach, Tibor Sloboda, Kristián Košťál, and Lukas Galke (2025). Guarded Query Routing for Large Language Models. ECAI.
Jacob Nielsen, Peter Schneider-Kamp, and Lukas Galke (2025). Continual Quantization-Aware Pre-Training: When to transition from 16-bit to 1.58-bit pre-training for BitNet language models? ACL Findings.
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

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

AI509: Natural Language Processing – Fall 2025, SDU (main lecturer)
AI508: Computer Vision – Fall 2025, SDU (co-lecturer)
DSK809: Deep Learning – Fall 2025, SDU (responsible)
AI506: Advanced Machine Learning – Spring 2025, SDU (main lecturer)
DM873/DS809: Deep Learning – Fall 2024, SDU (main lecturer)

Academic service

Program Chair: ICNLSP 2025
Program Committee: ACL, EMNLP, 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), …