Bachelor / Master Thesis

We are always looking for motivated students who want to write their BSc or MSc thesis with us. If you are interested in writing your thesis on a topic that aligns with our research interests, a broad range from low-level optimizations to rendering techniques and algorithms, feel free to contact us at any time.

The non-exhaustive list below is meant to provide you with an impression of what you could be working on with us. You will not have to work on exactly one of those topics (although you could), they are rather meant to help you choose what you want to work on. If you have your own ideas for different topics, we are more than happy to discuss those with you as well!

Topics on Global Illumination and Algorithms

If you are interested in one of the following topics, or looking to work on something similar, contact Pascal Grittmann

Adapting Advanced Algorithms for (High Performance) Implementations

Many algorithms for complex lighting effects or improved per-sample efficiency are challenging to implement, in particular in a high performance setting. The goal of this thesis topic could be to implement an existing algorithm either in the cleanest and simplest way possible, or to optimize the implementation of an existing algorithm towards the requirements of the hardware.

Who is this topic for?

  • Students interested in software engineering, performance optimizations, or both

Useful skills (not hard requirements):

  • Experience with C++, parallel programming, GPUs (for performance optimization)
  • Experience with programming and software design (for software engineering)

Machine Learning in Rendering

In recent years, machine learning methods have started to see use in the rendering community. For instance, machine learning is used to learn importance sampling distributions for Monte Carlo integration. Portable high performance kernels for mixture fitting could be of great use for researchers looking into this topic. Also, finding better representations for learned sampling distributions or faster algorithms to fit distributions to the data could be potential thesis topics.

Who is this topic for?

  • Students interested in rendering and machine learning

Useful skills (not hard requirements):

  • Lectures: Computer graphics and/or Realistic Image Synthesis
  • Experience with C++
  • Experience with machine learning

Suggested reading materials:

Tools for Debugging and Experimenting with Renderers

Research in rendering requires to frequently implement wild ideas and play around with them. Of course, this results in many hours spent debugging, waiting for rendering to finish, or waiting for the compiler to finish. This workflow could be greatly improved with debugging and visualization tools for rendering. For instance, visualizing individual paths, or groups thereof, and inspecting how their image contribution was computed can help to identify bugs in the implementation, or shortcomings of an algorithm.

Another interesting direction could also be to come up with tools that can assist a researcher when experimenting with importance sampling, or multiple importance sampling techniques. To that end, a user interface could be developed to alter importance sampling distributions and interactively display the resulting rendered images, or to modify the multiple importance sampling weights and interactively compare the impact of different strategies.

A completely different approach could also be to design a renderer that is partially implemented in a language like Python, for quick and dirty experiments with wild research ideas, that makes use of fast kernels for ray tracing, shading, and other tasks. The goal of such a system would be to strike a balance between supporting quick prototyping and experimentation, and reasonable performance and rendering times.

Who is this topic for?

  • Students interested in visualization and user interfaces

Useful skills (not hard requirements):

  • Python or other scripting languages
  • User interface design and visualization