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 Suitable topic candidates are shown in the following list, which is not meant to be complete though:

  • Detecting Hidden Meaning in Stock Images
  • Extracting Large-Scale Multimodal Datasets From Web Archives
  • Manipulating Embeddings of Stable Diffusion Prompts
  • Partitioning and Reconstructing Text Embeddings for Bias Mitigation and Authorship Analysis
  • Query Obfuscation for Dense Retrieval Models

Ongoing Theses

  • Halle
    • Erik Reuter. Interdocument-Aware Learning-to-Rank Using a Long Document Transformer (supervised by Ferdinand Schlatt)
    • Jan Heinrich Reimer. Health-Related Information Retrieval (supervised by Alexander Bonarenko, Maik Fröbe, and Matthias Hagen)
    • Max Henze. Simulation von Suchanfragen durch Anchortext (supervised by Maik Fröbe, Sebastian Günther, and Matthias Hagen)
  • Jena
    • Niklas Rausch. Multi-Task Learning with IR Axioms (supervised by Maik Fröbe, Alexander Bonarenko, and Matthias Hagen)
  • Leipzig
    • Thomas Abel. Comparative Scholar: Exploiting Pairwise Neural Networks for High-Recall Literature Search (supervised by Maik Fröbe, Lukas Gienapp)
    • Jonas Stahl. Adapting Sentence Embeddings to OCR erroneous data (supervised by Kim Bürgl)
    • Yaowei Zhang. Semi-automatic Knowledge Graph Authoring to Facilitate Retrieval of Expert Knowledge (supervised by Marcel Gohsen)
    • Leon Naumov. Last but not Least: Avoiding and Explicating Biases in Spoken Lists of Arguments (supervised by Johannes Kiesel)
    • Dominik Schwabe. Unsupervised Frame Identification in Argumentative Discussions (supervised by Shahbaz Syed and Khalid Al-Khatib)
    • Ahmad Dawar Hakimi. Contextualized Summarization of Scholarly Documents (supervised by Shahbaz Syed and Khalid Al-Khatib)
    • Deniz Simsek. Verbalizing Entity-based Answers in Conversational QA-Systems (supervised by Marcel Gohsen and Johannes Kiesel)
    • Simon Kleine. How we Argue: A Study of Vocal Argument-seeking Conversations (supervised by Johannes Kiesel)
    • Gabriel Huppenbauer. Context Dynamics of the Term Sustainability (supervised by Christian Kahmann)
    • Christian Staudte. Building a Large-scale Argumentation Graph (supervised by Khalid Al-Khatib)
    • Eric Schmidt. Identifying Debating Strategies on Wikipedia (supervised by Khalid Al-Khatib)
    • Nicolas Handke. What's your Point? Identifying Values in Arguments (supervised by Johannes Kiesel)
    • Yiwen Cao. Mapping travel routes based on travelogue narrative (supervised by Andreas Niekler and Magdalena Wolska)
    • Jonas Richter. Knowledge Graph of resistance network in Nazi Germany (supervised by Andreas Niekler and Christian Kahmann)
    • Clemens Schöne. Aquiring corpora with triggering content (supervised by Andreas Niekler and Magdalena Wolska)
    • Roy Rodney. A Web-based Implementation of the Netspeak Wordgraph (supervised by Tariq Youssef)
    • Hannes Winkler. Digital Monitor of Saxony (supervised by Andreas Niekler)
    • Markus Kobold. Etymological data from Wiktionary as a graph (supervised by Thomas Efer)
    • Wolfgang Kircheis. Analyzing the History Section of Wikipedia Articles. (supervised by Martin Potthast)
    • Maximus Germer. Chess Report Generation with Data-to-text (supervised by Janos Borst and Andreas Niekler)
    • Cariem El Wakil. Training a TTS Model with custom speech data for Galileofication. (supervised by Andreas Niekler)
    • Mathias Halbauer. Investigating Paneling and Sampling Techniques to Approximate Polling Data through Social Media. (supervised by Matti Wiegmann)
    • Bernhard Jung. Early Hype Detection - Detecting and Tracking Investment Hypes on Reddit. (supervised by Matti Wiegmann, Erik Körner, and Michael Völske)
    • Moritz Brunsch. Multi-Label Active Learning with Many Irrelevant Examples (supervised by Christopher Schröder)
    • Nils Schröder. Short Text Classification (supervised by Christian Kahmann and Christopher Schröder)
    • Karl Hase. Statistical Bootstrap Tests with Redundant Data (supervised by Maik Fröbe)
    • Charly Zimmer. Improving Causal Relation Extraction from the Web (supervised by Ferdinand Schlatt)
    • Gregor Pfänder. Automatic Data Extraction for Metanalyses from Biomedical Publications (supervised by Ferdinand Schlatt)
  • Weimar
    • Ludwig Lorenz. Searching Personal Web Archives (supervised by Johannes Kiesel)
    • Sanket Gupta. Advancing and Benchmarking Large-Scale Content Extraction from the Web (supervised by Janek Bevendorff, Johannes Kiesel, and Nikolay Kolyada)
    • Oliver Singler. Quantifying evidence of poetry perception based on physiological response to recital (supervised by Jan Ehlers and Magdalena Wolska)

Resources for Students


Dear prospective PhD student, unsolicited applications to the Webis group ( 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 Halle, Leipzig, Paderborn, 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