Project Opportunities

If you are interested in working with me on a senior project, or for your culminating experience of your master’s degree (project or thesis), here is a list of projects that I am currently working on and considering starting. If any of them sound interesting, reach out to discuss the concrete topic in more detail.

VR Lab (Spring only)

Throughout the spring semester, interested students can work in groups of 3-5 students to develop VR games/experiences. The concrete specifications for each individual game/experience is open to student ideas, but a key goal is to make use of the capabilities offered by a Virtual Reality environment. In past years, we have investigated novel interaction modes, as well as applications of VR for immersive training, and education. You can find a list of previous projects with demo videos here.

Procedural Content Generation in Minecraft

The Generative Design in Minecraft (GDMC) Competition, which has been held annually since 2018, is “about writing an algorithm that can create a settlement for a given, unknown Minecraft map.” For this project, we are working on developing a complete settlement generator, consisting of map analysis, layout and zoning, building generation, variation, ensuring the usability and plausibility of the settlement, etc. We are building on a newly developed, grammar-based approach, which we presented in a recent publication, and which was then further expanded upon. However, there are still many tasks that remain to be done, including generating individual buildings, parks, farms, and other areas, integrating the various components into a single generator, improving aesthetics (e.g. by placing lights), etc.

Procedural Level Generation for a VR Rhythm game

Ragnarock is a VR rhythm game, where players have to hit drums in sync with a given song. For a given song, there are typically multiple levels of difficulty available, which differ in the frequency and variation in the drum patterns. While the game supports custom, fan-created levels, each such level has to be created by hand. For this project we are looking into developing an automated approach to generating these levels. Since a large number of custom levels has already been created by fans, we can use information gained from these, such as which patterns are typically used, as the basis of our generator. For this project we will be working on extracting audio-information from a given song, matching it with the appropriate patterns, and then also ensuring that the generated levels are of an appropriate difficulty. As the game supports and API for in-game monitoring, eventually we will also want to utilize this information to tailor each level to individual players.

Digital Twin

This project is a cooperation with Dr. Sotoudeh from the Department of Aerospace Engineering. The goal of the project is to build a (physical) UAV, equipped with sensors that monitor its status while it is in flight, and report this information back to the ground. On the ground, we have a digital version of that same UAV, in the form of a Unity application, with various simulation models corresponding that represent the UAV in various theoretical states. A decision making module determines which simulation model best corresponds to the current state of the physical asset, and the Unity application then uses this simulated version to allow users to perform e.g. a what-if analysis for the future performance of the aircraft. For this project, we have an initial prototype, corresponding to a wing, and are currently in the process of building, simulating, and modeling a full aircraft.

Generative Models: Applications and Limitations

Generative Models, such as ChatGPT, have seen a recent surge in interest, although they have existed for many years. For this project, we are interested in two aspects of recent advances in the field: First, the ability of e.g. ChatGPT to produce text is impressive at first glance, but how to use this text in longer-form environments is still an open question. For this part of the project, we want to look at how a generative text model could be used to write long-form text, e.g. a novel, in a way that is consistent and coherent. However, while it is known that generative models may produce flat-out incorrect or made-up responses, and this can lead to real-world consequences (e.g. when using ChatGPT to produce court filings), even information that is not flat-out “wrong” may still not be biased in an undesirable way. For the second part of this project we are therefore investigating biases in LLMs, and how these could even be measured and detected.

Suggest your own

I am always open to student suggestions that are related to my research interests: My main research area is AI in games, with a particular focus on the interaction of games, AI agents and humans, such as producing artifacts for human consumption, or novel ways of interaction, e.g. in VR.

Past Projects


Building Intelligent Agents for Hanabi


Practical Specification of Belief Manipulation in Games


Building Intelligent Agents for Pandemic


A planning and plan recognition component for Unity

Worldle: Geography guessing game