👋️ Profile

I am a Ph.D. candidate at Heinrich Heine University Düsseldorf (defense scheduled for late 2025), a researcher at the Heine Center for Artificial Intelligence and Data Science (HeiCAD), and a guest researcher at GESIS, the Leibniz Institute for the Social Sciences.

My research focuses on Natural Language Processing (NLP), Machine Learning (ML), and Large Language Models (LLMs), with particular emphasis on argumentation, social media analysis, and the development of LLMs capable of human-like reasoning, language understanding, and cross-domain generalization.

In addition to my academic work, I actively contribute as a partner to the HeiCAD initiative “AI for All,” which is committed to accessible and inclusive education about Artificial Intelligence (AI) for everyone.

Motivated by my interest in language, communication, and culture, I have been learning Thai weekly at a local language school since the start of my Ph.D. in 2021.

🎓 Education

Ph.D. in Computer Science
2021–Present | Heinrich Heine University Düsseldorf
(Expected defense: Late 2025)

M.Sc. in Computer Science
2019–2021 | Heinrich Heine University Düsseldorf
Final Grade: 1.1 (Very Good)

B.Sc. in Computer Science
2016–2019 | Heinrich Heine University Düsseldorf
Final Grade: 2.5 (Good)

💼 Professional Experience

Research Associate
2021–Present | Heinrich Heine University Düsseldorf

Partner in the e-learning initiative “AI for All”
Lecturer: Computer Science for Non-Computer Scientists

Research Assistant
2019–2021 | Heinrich Heine University Düsseldorf

Python Developer, Institute for Computer Networks and Communication Systems
Lecturer: Computer Science for Non-Computer Scientists

Student Assistant
2016–2019 | Heinrich Heine University Düsseldorf

Python Developer, Institute for Computer Networks and Communication Systems
Instructor: Java Development, C and NASM Assembler

🧪 Skills

💻 Programming Languages & Scripting

_{Also worked with: Bash, C, C++, Java, JavaScript, JSON, NASM, Markdown}

🤖 Machine Learning & NLP

_{Also worked with: LoRA, NLTK, NumPy, PEFT, RAG, pandas}

🧰 Frameworks & DevOps

🗃️ Databases & Search

🧱 Development Tools

_{Also worked with: IntelliJ IDEA, iTerm2, nano, vim, zsh}

📦 Package Managers

💽 Operating Systems

🌐 Languages

German 🇩🇪 – Native
English 🇬🇧 🇺🇸 – Fluent
Thai 🇹🇭 – Basic

📚 Publications

🥇 Top-Tier Conferences & Journals

Feger, M., Boland, K., & Dietze, S. (2025). Limited Generalizability in Argument Mining. ACL 2025 (To be published).
Weber, S., Feger, M., & Pilgermann, M. (2024). A Unified Evaluation Approach for LLM Honeypots. IEEE Access.
Feger, M., & Dietze, S. (2024). BERTweet’s TACO Fiesta: Argument Mining on Twitter. NAACL 2024.
Feger, M., & Dietze, S. (2024). TACO — Twitter Arguments from Conversations. LREC-COLING 2024.

🥈 Other Peer-Reviewed Publications

Braun, M., & Feger, M. (2025). TextLabel: A Web App for Text Annotation. HCII 2025 (To be published).
Zelle, Y., Grison, T., & Feger, M. (2023). SciTok – Web Scraping Tool for Social Science. HCII 2023.
Steimann, J., Feger, M., & Mauve, M. (2022). Inspiring Perspectives in Comment Sections. HCII 2022.
Feger, M., Steimann, J., & Meter, C. (2020). Structure or Content? Argument Relevance. COMMA 2020.

💻 Selected GitHub Projects

🎓✨ Featured AI Education Videos

🌱 Machine Learning & Sustainability Tools

🎥 Watch More of my AI Learning Videos

🤖 Explainable, Hybrid, and Robust AI
👩‍💻 Programming Neural Networks from Scratch
📝 Text Processing with Transformers
🖼️ Image Processing with Convolutional Neural Networks

📚 Or Explore the Full Lecture Series