M.Sc. Computational Linguistics, LMU Munich
I am a computational linguist interested in large language models, natural language processing, and the evaluation of AI systems, with a focus on understanding and analysing model behaviour.
About
I recently completed my M.Sc. in Computational Linguistics at LMU Munich.
My academic work has focused on natural language processing, machine learning, deep learning, generative AI, and the analysis of language model behaviour. I am particularly interested in making AI systems more interpretable and human-centered.
I enjoy approaching complex problems analytically, exploring different methods, and communicating technical findings clearly.
Selected Projects
LLM Behaviour Analysis
Master’s Thesis · 2026
Extended existing methodology for systematically identifying and analyzing behavioral differences between large language models.
- Extended and adapted an interpretable data-mining framework by incorporating novel LLM-derived features.
- Combined linguistic features with model-assisted analysis to analyze output variations.
- Evaluated the approach across controlled benchmarks and real-world application scenarios.
Research paper in preparation.
LLM-as-a-Judge Robustness & Evaluation
Trustworthy & Data-Centric AI Project · 2026
Evaluated the reliability and robustness of automated LLM-based evaluation frameworks.
- Analysed how variations in prompts and system conditions affect the consistency of model judgments.
- Identified failure modes in automated evaluation setups to improve benchmark reliability.
Education
M.Sc. Computational Linguistics LMU Munich · 2024–2026
Transition Year in Computational Linguistics (B.Sc. Level) LMU Munich · 2023–2024
B.A. Intercultural Applied Linguistics University of Augsburg · 2019–2024
Skills
AI & Language Technology: Natural Language Processing, Large Language Models (LLMs), RAG, Prompt Engineering, LLM Evaluation, Transformers
Data & Research: Data Mining, Model Evaluation, Statistical Analysis, Experimental Design, Clustering, Information Retrieval
Frameworks & Tools: Python, PyTorch, Hugging Face, scikit-learn, pandas, NumPy, Git, Jupyter, LaTeX