👋️ About Me

I am a Research Associate at Heinrich Heine University Düsseldorf, a researcher at the Heine Center for Artificial Intelligence and Data Science (HeiCAD), and a Visiting Researcher at GESIS – Leibniz Institute for the Social Sciences.

My research focuses on Artificial Intelligence (AI), Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI (GenAI). I am particularly interested in how AI systems can learn to reason, understand language, and generalize across domains. My work spans computational argumentation, social media analysis, Conversational AI, and the development of intelligent systems capable of human-like reasoning and language understanding.

With more than five years of research experience, I have developed and evaluated models for NLP and speech-related applications.

My research has been published at leading venues such as ACL, NAACL, and LREC-COLING, and I actively contribute to the community as a reviewer for top-tier NLP conferences.

Beyond research, I enjoy mentoring students, developing educational content, and teaching Python programming and AI-related topics to make technology more accessible to broader audiences.

My long-term research vision is to contribute to the development of AI systems that move beyond pattern matching toward human-like reasoning, language abilities, and generalization across diverse domains and tasks.

🎓 Education

Ph.D. in Computer Science
2021–2026 | Heinrich Heine University Düsseldorf
Final Grade: 0.5 (Summa Cum Laude ≈ GPA 4.0 of 4.0)

M.Sc. in Computer Science
2019–2021 | Heinrich Heine University Düsseldorf
Final Grade: 1.1 (Very Good ≈ GPA 3.7 - 4.0 of 4.0)

B.Sc. in Computer Science
2016–2019 | Heinrich Heine University Düsseldorf
Final Grade: 2.5 (Good ≈ GPA 3.0 - 3.3 of 4.0)

💼 Professional Experience

Research Associate
2021–Present | Heinrich Heine University Düsseldorf

Conducted research in Artificial Intelligence, Natural Language Processing, Generative AI, and Conversational AI
Contributed to a DFG-funded international AI research project
Supervised and mentored Bachelor’s, Master’s, and Ph.D. students
Developed educational content for the e-learning initiative AI for All
Lecturer: Computer Science for Non-Computer Scientists

Research Assistant
2019–2021 | Heinrich Heine University Düsseldorf

Developed Python-based research software and data analysis tools
Lecturer: Computer Science for Non-Computer Scientists

Student Research Assistant
2016–2019 | Heinrich Heine University Düsseldorf

Developed Python-based online conversation platforms for research
Teaching Assistant: Professional Software Development with Java
Teaching Assistant: C and NASM Assembler

🤓 Committee Lead

CLEF 2026 - Generalizability of Argument Identification in Context.
Feger, M., Boland, K., Romberg, J., & Dietze, S.

📚 Publications

🎓 Dissertation

2026 - The Limits of Progress: Understanding the Performance of State-of-the-Art Language Models in Argument Mining.
Grade: 0.5 (Summa Cum Laude ≈ GPA 4.0 of 4.0)

🔬 Master’s Thesis

2021 - Online Argumentation and Social Media: What They Can Learn from Each Other.
Grade: 1.0 (Very Good ≈ GPA 3.7 - 4.0 of 4.0)

📝 Bachelor’s Thesis

2018 - Comparison of Recommendation Systems.
Grade: 1.0 (Very Good ≈ GPA 3.7 - 4.0 of 4.0)

🥇 Top-Tier Conferences & Journals

ECIR 2026 - Overview of Touché 2026: Argumentation Systems.
Kiesel, J., Feger, M., Hagen, T., Heineking, S., Heinrich, M., Fröbe, M., Boland, K., Pertsch, W., Romberg, J., Zelch, I., Dietze, S., Hagen, M., Potthast, M., & Stein, B.
ACL 2025 - Limited Generalizability in Argument Mining: State-Of-The-Art Models Learn Datasets, Not Arguments.
Feger, M., Boland, K., & Dietze, S.
IEEE Access 2024 - Don’t Stop Believin’: A Unified Evaluation Approach for LLM Honeypots.
Weber, S., Feger, M., & Pilgermann, M.
NAACL 2024 - BERTweet’s TACO Fiesta: Contrasting Flavors On The Path Of Inference And Information-Driven Argument Mining On Twitter.
Feger, M., & Dietze, S.
LREC-COLING 2024 - TACO — Twitter Arguments from Conversations.
Feger, M., & Dietze, S.

🥈 Other Peer-Reviewed Publications

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

🎓✨ Featured AI Education Videos

🌱 Foundations of Machine Learning and Transformer Models

🎥 Watch More of my AI Education Videos

📚 Or Explore the Full Lecture Series

🧪 Technical Skills

💻 Programming Languages

Python, SQL, Java, JavaScript, HTML, C/C++, NASM

🤖 Artificial Intelligence, Deep Learning & NLP

PyTorch, TensorFlow, Transformers, Hugging Face Ecosystem, Conversational AI, Information Retrieval, Speech Recognition (ASR), Whisper, Argument Mining

🧠 Language Models & Generative AI

LLMs, SLMs, Foundation Models, OpenAI API, LangChain, RAG, Agentic AI & MCP, LoRA/PEFT, Prompt Engineering, Evaluation & Benchmarking, Lightning AI, Together AI, vLLM

📊 Machine Learning & Data Science

scikit-learn, pandas, NumPy, SciPy, Statistical Analysis & Testing, Model Evaluation, Data Mining

🗃️ Databases & Search

PostgreSQL, Neo4j, Elasticsearch, SQLite

⚙️ Software Engineering, MLOps & AI Infrastructure

Git, Docker, FastAPI, Django, CI/CD, TDD, GPU-Accelerated Training & Inference

🌐 Languages

German 🇩🇪 – Native
English 🇬🇧 🇺🇸 – Full Professional Proficiency
Thai 🇹🇭 – Conversational Proficiency