Thesis Topics

Topics for bachelor and master thesis will be in one of the following areas:

1. Visualizing Data in Virtual and Augmented Reality

Developing new methods for exploring and analyzing data in virtual and augmented reality presents many opportunities and challenges, both in terms of software development and design inspiration. There are various hardware options, from Google Cardboard to Oculus Rift. Taking part in this challenge demands programming skills as well as creativity. A basic VR or AR application for exploring a specific type of (open) data will be developed by the student. The use of a platform-independent kit such as A-Frame is essential, as the application will be compared in a small user study to its non-VR version in order to identify advantages and disadvantages of the visualization method implemented. Details will be discussed with supervisor.

Research problem: How can AR and VR be used to improve exploration of data?

Some References:

2. Text mining & machine learning

April 2022: Our institute has recently acquired high performance GPU units which are currently being prepared for student use in thesis projects. Hopefully there will soon be news on how to run your code on the GPU server; however, since it is highly recommended to use a high-level framework such as Keras for developing your deep learning application the changes required to go from CPU to GPU computing will be minimal and should be limited to a few definitions in a config file. This means that you can start developing right now using your PC or notebook, or the Jupyter notebook server of the department, with a smaller subset of the training data; when you later transition to the GPU server more performance will mean larger datasets become feasible.

For an introduction: Minqing Hu, Bing Liu, "Mining and summarizing customer reviews", KDD '04, pp. 168-177

3. Aggregation of preferences

Introduction: Donald Saari, Decisions and Elections , Cambridge University Press, 2001

The areas above provide outlines, specific topics will be much more narrow and are agreed on individually. You can suggest a topic outside the areas above; of course I can only supervise if I feel qualified. Otherwise, I will just refer you to a colleague.

The aim of the work

When investigating questions, programming and basic statistical knowledge should be used to implement the approach you have described and to evaluate results (Python, C / C ++, Perl, PHP, Java; R).

The thesis should deal with a problem in a scientific way - no new contributions to science have to be made but the mastery of the scientific working method should be shown, esp.

Structure of the work

The work should be structured roughly like this:

The word "I" is not commonly used in scientific texts; rather, the passive form or some other formulations are used, such as "In this work .. is explored". If absolutely necessary you can use "the author" instead of "I".

The purpose of science is to expand knowledge and provide verifiable explanations about the world. When you write code it is impossible for other people to verify or extend your work without access to your code: create a free public github repository (or some similar publicly accessible site) for your work and provide a link in the thesis.

The goal must be reproducible research which is easier to achieve using non-proprietary and generally available open and free resources rather than commercial software or services (such as software encumbered by non-free licenses or data access only available for paid subscription).

Difference between bachelor and master: For a bachelor thesis, scope and complexity requirements are lower; a rough rule of thumb for the number of pages:

LaTeX and BibTeX

LaTeX is used for the thesis, which is the standard in many scientific fields for good reason. Cross-references, tables and graphics are no problem even in very large documents. Latex provides basic citation support, but managing references with a choice of consistent format is much easier with BibTeX.

On the web you will find a large number of short introductions and sample documents for LaTeX and BibTeX, the low initial effort is worthwhile. You can install Latex on your own PC, but it is probably easier to use on Single user is free, all conceivable packages including Bibtex are installed, and it works in every web browser. There is no need for subtleties in the layout. Latex documentclass article and bibtexstyle plain are sufficient.

English is the language of choice. Pay attention to reasonably correct grammar; it doesn't have to be Shakespeare, but we want to understand what you're saying. Use the spell check!

Plagiarism and Copyright

Plagiarism is the use of a significant part of a text (more than a few words), a table, an image, or other type of content without citing the source and thus giving the impression that this is your own achievement. The University uses software to automatically check for plagiarism. Do not copy text and then change it slightly; this can also be detected. Do not use large amounts of text from other sources, even when citing all the sources. Tell your story in your own words.

It is better to cite too much than too little. A Latex citation such as "\cite{Knuth80}" only results in a short reference such as "[1]" (when using bibtexstyle plain) in the finished document. This is done quickly and does not interfere with reading, even if there are 20 citations on each page. Do not risk a plagiarism charge; even when discovered many years later the consequences for your career can be disastrous.

Also note the WU guidelines for plagiarism

Copyright protects original works of authorship fixed in any tangible medium of expression. This is roughly the US definition, the Austrian one is similar (tangible expression of independent creative achievement). The requirements for originality tend to be moderate. Copyright exists automatically; a note such as (c) or © or some registration are not necessary (but tend to support a case).

Copyright infringement and plagiarism are two different things. Providing citations for content you are copying does not avoid liability for copyright infringement. In academic publications the subject of copyright is often treated lightly, especially when it comes to using images from other sources. It is recommended that you do not rely on fair use; only use content from other sources when you have explicit permission, e.g. when the copyright owner has explicitly allowed certain types of use by providing a statement to that effect. You can always illustrate something by creating your own diagram (distinctly different from other sources).


  1. Start: email me your title and abstract. Make the title very specific; it should clearly describe the scope of the work. That scope should be as narrow as possible. Add a short abstract: what you intend to do, how, and what you expect as results - just a few sentences.
  2. I will give you feedback on title and abstract and enter the thesis into the BACH/LPIS system.
  3. Roughly one month later: send me an update of your current work, so I can give you more feedback as you go.
  4. Hopefully not much more than 4-6 months later: upload your completed work to the Learn system for plagiarism check.
  5. I will read this version (allow for a week or two) and give you detailed feedback.
  6. Update your work as suggested in my comments and submit it again (exactly the same Learn upload procedure).
  7. Finish: I enter the grade in the BACH/LPIS system.

Any time in between feel free to contact me for more feedback and hints, especially when you are stuck with technical or programming challenges. Even in distance mode we can always have a little Jitsi screen sharing session to solve problems.

See also

Johann Mitloehner, 2021