We supervise student theses with a research-first, publication-oriented mindset. The current topics are described (incl. contact person) on the linked ScaDS.AI pages below. The page /student-outcomes/ provides selected examples of student-led papers, datasets, code, and demos.
Please read first: /how-we-work/ (publication mindset, expectations).
Quick answers: /faq/.
| No. | Topic | Field(s) | Contact |
| 1 | LLM-Augmented Knowledge Graph Search & Question Answering with MCP Servers on SemOpenAlex | Scholarly LLMs, RAG/QA, Knowledge Graphs | Michael Färber; A F M Mohimenul Joaa |
| 2 | Transforming Court Decisions into Plain Language with Generative AI | NLP, Text Simplification, Legal AI | Michael Färber |
| 3 | Advanced Multimodal Learning for Electronic Health Records: Toward Comprehensive and Interpretable Clinical Intelligence | Multimodal ML, Health / EHR | Zhan Qu |
| 4 | LLMs for Scientific Discovery: Designing AI Systems That Generate New Scientific Theories | Scholarly LLMs, Scientific Discovery | Michael Färber |
| 5 | Building Creative Large Language Models | LLMs, Generative AI | Michael Färber |
| 6 | AI-Moderated Political Debates: Simulating Democratic Discourse with Multi-Agent LLM Systems | Multi-agent LLMs, NLP | Michael Färber |
| 7 | Detecting and Mitigating Hate Speech with Large Language Models: Evaluating Strategies and Ethical Considerations | LLMs, Safety, Ethics | Shuzhou Yuan |
| 8 | GPT-3, BERT & Co.: When to use which language model? | LLMs, NLP, Evaluation | Michael Färber |
| 9 | Using Quantum Computing in Natural Language Processing | Quantum Computing, NLP | Michael Färber |
| 10 | Fusing RDF Knowledge Graphs with Deep Learning for Advanced Recommender Systems | Knowledge Graphs (RDF), Graph ML | Michael Färber |
| 11 | Extending the RDF Knowledge Graph SemOpenAlex.org | Knowledge Graphs (RDF), SemOpenAlex | Michael Färber |
| 12 | Stock Market Predictions through Deep Learning | Machine Learning, Finance | Michael Färber |
| 13 | Copyright and Generative AI: Does Reproduction Imply Memorization? | LLMs, Memorization, Copyright / Legal AI | Michael Färber |
| 14 | Claim Detection in Sensitive and Multilingual Domains | NLP, Fact-Checking, Multilingual NLP | Marina Litvak |
| 15 | How Close Are Information Retrieval (IR) and Natural Language Processing (NLP)? A Study of Top-Tier Conferences | Information Retrieval, NLP, Bibliometrics | Marina Litvak |
| 16 | Text Anonymization: Robustness Against LLM Attacks | NLP, Privacy, LLM Security | Marina Litvak |
| 17 | Context-Aware Code Development with AI Assistance | LLMs for Code, RAG, Software Engineering | Marina Litvak |
| 18 | Text Simplification: A Case Study with Agentic AI | Agentic AI, Text Simplification, NLP | Marina Litvak |
How to apply:
Please choose a topic and email the listed contact person. Before doing so, please also have a look at /student-outcomes/, /how-we-work/, and /faq/.
To keep the process efficient, please include:
- short CV
- transcript of records (and, if applicable, transcript of your bachelor’s)
- short statement (a few sentences) on your skills, your motivation for the topic, and your planned thesis starting date
- if applicable: PDF of your bachelor’s thesis
- optional but helpful: GitHub/portfolio or a pointer to relevant past projects
We are also open to supervising highly motivated students from other German universities (and international students). Please ensure that any formal requirements (e.g., examiner requirements) are clarified with your home institution.
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