Open Thesis Topics

Students who are eager to develop their skills by doing a research-oriented thesis in our group should mail their interests to webis@listserv.uni-weimar.de. Suitable topic candidates are shown in the following list. Your own suggestions for topics are also welcome, for which you can draw inspiration from our recent publications.

  • We currently have no open topics. You can always let us know if you're interested.

Open Student Assistant Topics

Students who want to improve their skills and work with us can apply for a position as a student assistant at webis@listserv.uni-weimar.de. We are currently looking for assistants to work on the following topics:

  • We currently have no open topics. You can always let us know if you're interested.

Ongoing Theses

  • Halle
    • Building Medical Knowledge Graphs for Knowledge Injection in LLMs (supervised by Alexander Bondarenko and Jan Heinrich Merker)
  • Jena
    • Testing the Limits of Multi-Vector Bi-Encoder Models (supervised by Ferdinand Schlatt)
    • Microblog Retrieval on the Fediverse (supervised by Jan Heinrich Merker and Matti Wiegmann)
    • Analyzing the Effectiveness of Community Self-moderation on the Fediverse (supervised by Jan Heinrich Merker and Matti Wiegmann)
    • Large-scale Query Log Analyses (supervised by Jan Heinrich Merker)
    • Dense Boolean Retrieval for Systematic Reviews (supervised by Ferdinand Schlatt)
    • Improving Learned Lexical Retrieval Models by Removing Lexical Dependencies (supervised by Ferdinand Schlatt)
    • Combining Query Segmentation with Subword Tokenization in Dense Retrieval (supervised by Ferdinand Schlatt and Maik Fröbe)
    • Reducing the Size of Dense Retrieval Indexes by Removing Unimportant Terms (supervised by Ferdinand Schlatt)
    • Estimating the Trustworthiness of Wikipedia Articles (supervised by Jan Heinrich Merker and Matthias Hagen)
    • Argument Mining in the AQL (supervised by Ines Zelch)
  • Leipzig
    • Optimizing Prompts for Text-To-Image Generation in Discrete Token Space (supervised by Niklas Deckers)
    • Extracting negated causal statements (supervised by Tim Hagen)
    • Facets of complexity in scholarly political language (supervised by Magdalena Wolska)
    • Simplifying the language of political argumentation (supervised by Magdalena Wolska)
    • Text2SQL. Exploring Relational Databases with Natural Language User Interfaces (supervised by Tim Gollub)
    • Psychological Features of Argumentation (supervised by Maximilian Heinrich)
    • Lightweight Passage Re-ranking Using Embeddings from Pre-trained Language Models (supervised by Ferdinand Schlatt and Harry Scells)
    • Logical Features of Neural Networks (supervised by Maximilian Heinrich)
    • Classification of Multimodal Social Media Posts (supervised by Tim Gollub)
    • Active Learning for Text Classification (supervised by Christian Kahmann and Christopher Schröder)
    • Incorporating Knowledge Graph Embeddings in Large Language Models (supervised by Ferdinand Schlatt)
    • Normdaten-Disambiguierung und Reconciliation auf Korpusdaten (supervised by Erik Körner and Felix Helfer)
    • Statistical Bootstrap Tests with Redundant Data (supervised by Maik Fröbe)
    • Mining Trigger Warnings from the Web and Social Media (supervised by Matti Wiegmann)
  • Weimar
    • How Humans Detect Cloned Voices (supervised by Johannes Kiesel and Marcel Gohsen)
    • Automated Conversational Search Evaluation (supervised by Nailia Mirzakhmedova and Johannes Kiesel)
    • Language Model Evaluation Game (supervised by Johannes Kiesel)
    • Retrieval Augmented Generation for Enhanced Access to Industrial Documentation (supervised by Tim Gollub)
    • Chart Retrieval for Arguments (supervised by Johannes Kiesel)
    • Mimicking Personas of Dialog Participants with Large Language Models (supervised by Marcel Gohsen)
    • Personalizing Harm Reduction in Text Generation (supervised by Marcel Gohsen and Matti Wiegmann)
    • Personalizing Question Answering (supervised by Marcel Gohsen and Matti Wiegmann)
    • Character-Driven Story Generation Through Character Networks (supervised by Marcel Gohsen)
    • Health-Related Queries in Large-Scale Query Logs (supervised by Jan Heinrich Merker)
    • Information Extraction from Academic Mailing Lists (supervised by Tim Gollub)
    • Topic Segmentation with Large Language Models (supervised by Johannes Kiesel)
    • Retrieval Augmented Generation for the IR-Anthology (supervised by Tim Gollub)
    • Mining Linked Data on Web Scale (supervised by Nikolay Kolyada)
    • Efficient and Effective Neural Translation Language Model for Search (supervised by Harry Scells)
    • Rating the Degree of Search Engine Optimization of Websites (supervised by Janek Bevendorff and Matti Wiegmann)

Resources for Students

Vacancies

Dear prospective PhD student, unsolicited applications to the Webis group (webis.de) are welcome. However, we cannot promise that open positions are available at the time of your application.

The Webis Group is a tightly cooperating research network, formed by computer science chairs at the universities of Groningen, Hannover, Jena, Kassel, Leipzig, and Weimar. Our mission is to tackle challenges of the information society by conducting basic and applied research with the goal of prototyping and evaluating future information systems. We are an experienced research group where team spirit and active collaboration has top priority. We are looking for open-minded graduates and PhDs who want to develop both as a researcher and as a person. The working language of our group is English; fluency in German is not required.

Interested students should have finished either a master or a PhD in computer science, mathematics, or a related field with excellent or very good grades. A solid background in mathematics and statistics is expected—as well as very good programming skills.

Benno Stein
Bauhaus-Universität Weimar
On behalf of the Webis group

Email: webis@listserv.uni-weimar.de
Web: webis.de