Topic Areas
We are continuously offering Bachelor and Master thesis topics in the following areas:
Efficient approximate probabilistic inference algorithms (e.g., variational inference, message-passing, sampling-based inference, mixed-inference)
Approximate computing, in particular focused on streaming-based machine learning algorithms (e.g., approximate perceptron learning, approximate message passing)
- Modelling and inference of physical energy systems (e.g., electric battery models)
- Algorithm- and implementation-specific measures of statistical complexity (e.g., luckiness framework, compression framework)
If you want to write a master thesis at our group feel free to contact us for some topic ideas in the given areas. Of course, you can also come up with your own topic. You can find the descriptions of all HPI bachelor projects here and the list of all HPI Master projects here.
Writing a thesis at our group
Writing the thesis usually includes the following five steps:
- Finding a topic together with an advisor (usually a PhD student or PostDoc).
- Choosing your second supervisor
- Writing a thesis proposal describing the main research problem and your approach. For details on the proposal, check out the proposal template of the Data Engineering Systems group.
- Registering the thesis with the Studienreferat after the proposal is accepted.
- Writing your thesis (this is the most fun part!) Please feel free to use the Overleaf thesis template from the Algorithm Engineering group.
Thesis submission
Once registered with the Studienreferat, the student has 6 months to submit the final version to both supervisors. Both supervisors then evaluate the thesis within 6 weeks. If necessary, a third examiner can be included in the process.
Thesis defense & presentation
The oral defense includes a graded 20-minute presentation and a 30-minute discussion with the evaluation commitee. The defenses are generally open for attendance by the community.
For all questions regarding a thesis at our group, just reach out to us.
