We are looking for a PhD student working on using large language models such as ChatGPT for robust AI planning. Contact: Jendrik Seipp


We offer interesting topics for master theses in the field of AI/ML with a focus on planning. If you are interested, please contact us by email. We will then find a topic that suits your interest and background. Here are some example topics:

Visualizing action plans with generative machine learning models

Generative models are now powerful enough to generate realistic images and videos from natural language texts (see e.g. Du et al.). In this project we want to test whether such deep learning models can be used to generate visualizations of action plans obtained with AI planners. The goal is to generate visualizations that are easy to understand for humans and that can be used to improve the plans.

Creating an email writing assistant

We want to compare different offline and online language models for the task of completing emails within the Thunderbird email client. Important challenges here will be to figure out how complex language models need to be and how much information from previous conversations we need to feed them to provide useful assistance. We want to find out whether we can obtain a freely-available privacy-preserving writing assistant. The ultimate aim is to obtain a Thunderbird add-on that assists users around the world in writing emails.

Learning to categorize emails

Within this project we want to create and compare different machine learning models that learn how to categorize incoming emails into folders. Accurate predictions will help Thunderbird users handle their mail faster. The main research challenge here is that the models will have to learn autonomously, starting without any knowledge about the user's email habits, and gradually becoming better at categorization over time.