Our research group offers you the possibility to write your theses with us at any time. You can either apply for one of the suggested topics or submit your own proposal, which should be related to one of our research areas. Theses can also be conducted in cooperation with a company.
If you would like to apply for a suggested topic, please send a brief description of your interest in the topic and your last transcript of records via email to the responsible supervisor.
If you would like to propose your own topic, please send a working title, a short description of your topic and your planned approach together with your last transcript of records via email to the researcher(s) of the respective research area.

If you would like to be updated when new topics are announced, as well as to access research materials, please join our StudOn group.

Open Theses Topics

Data-driven decision making on the shop floor – A state-of-the-art analysis

Language: German or English
Supervisor: Markus Schamberger

Data Valuation Methods for Cross-Silo Federated Learning Networks

Language: German or English
Supervisor: Kristina Müller

Formal Requirements

Before applying for a topic at our research group, please check the exam regulations of your specific study program regarding master thesis formal requirements (e.g., ECTS pre-requisite). If you have doubt please contact the responsible person of your study program directly.

For Master IIS students, there is no pre-requisite to do the master thesis with us. Nevertheless, we encourage students who may be interested to write their thesis with us, to first attend either our Business Intelligence lecture or one of our seminars.

Please note that students have to be matriculated while working on their master thesis.


    1. Exposé
      As soon as the topic is defined, you start working on the exposé. It consists of:
      • Motivation
      • Research question
      • Research design
      • Expected results
      • Preliminary list of references
    2. Registration

Once the exposé is approved, the topic can be officially registered. There are 6 months of official working time as per the rules of our faculty. This can be extended only after special circumstances usually requiring the submission of additional documents, such as doctor’s notice.

  1. Working Period
    • You are responsible for organizing regular meetings with your supervisor.
    • You should give a midterm presentation (10 to 15 minutes presentation plus 5 minutes questions) about halfway through your master thesis project.
    • You should give a final presentation (15 minutes presentation plus 10 minutes questions).
  2. Submission
    • You need to hand in two hard copies together with a CD or USB with all additional materials that have been used for the thesis (e.g., code, interview transcripts, references) directly to the examination office. Specific requirements for submission are usually stated with the registration confirmation from the examination office.
    • The thesis should be approximately 25,000 words (60-80 pages).


  • Word (english)
  • We are currently working on providing a LaTeX template.

Selected Supervised Theses

  • Trustworthy data sharing in healthcare: A blockchain-based concept and prototype (in cooperation with Swinburne University of Technology, Melbourne)
    Supervisor: Pavlina Kröckel
  • The business and patients value of trusted data sharing within and between stakeholders in healthcare – lessons learned from explorative studies on private blockchains in healthcare (in cooperation with Swinburne University of Technology, Melbourne)
    Supervisor: Pavlina Kröckel
  • The potential of NFTs in healthcare
    Supervisor: Pavlina Kröckel, co-supervised with Prof. Mathias Kraus
  • AutoML platform at Siemens: Benchmark and market placement
    Supervisor: Pavlina Kröckel
  • Open Government Data: Architecture and System Design for Enhancing Competitive Intelligence in the Medtech Industry
    Supervisor: Annika Lurz
  • Medical Diagnostics Platform: Development of an App for Deep Learning Based Diagnostics of Blood Samples Measured with Deformability Cytometry
    Supervisor: Annika Lurz
    Partner: Max Planck Institut for the Science of Light
  • Entwicklung und Evaluierung eines Vorgehensmodells für die Digitale Transformation: Eine Fallstudie aus der Intralogistik in der Elektronikfertigung
    Supervisor: Annika Lurz
    Partner: Siemens Healthineers
  • Patent Analysis in the MedTech Industry Using Natural Language Processing Approaches
    Supervisor: Annika Lurz
  • Agent-based Modeling of Dynamic Events: FAU Emergency Evacuation
    Supervisor: Annika Lurz
  • Understanding the Individual Value Creation Potential of Cross-Enterprise Collaboration in Federated Networks
    Supervisor: Kristina Müller
  • Requierement Analysis for a Technology Acceptance Method for Social Robots
    Supervisor: Nina Merz