With the increasing complexity of industrial control systems (ICS) in smart grids, the risk of cyber-attacks is also rising. To enhance the security and resilience of these systems, new approaches are needed for detecting and mitigating cyber incidents. This thesis develops a decision support system (DSS) designed to assess and recommend effective countermeasures against cyber ...
The aim of this thesis is to design, implement, and evaluate a machine learning-based system for detecting chatter in thin-walled workpieces during machining processes. By leveraging MLOps principles, the system will automate the data pipeline from sensor data acquisition to model deployment, ensuring a scalable and efficient workflow. Additionally, the integration of the system within ...
Real-time distributed information systems (RDIS) are designed to process, manage, and deliver data across interconnected components in distributed environments under strict timing constraints. In the context of public transportation, RDIS gathers information from heterogeneous data sources, such as buses and stations, to provide passengers with timely updates on schedules, delays, and operational changes through user ...
The growing adoption of electric vehicles (EVs) is reshaping power grids by introducing cybersecurity challenges that could be exploited to target both the EV and the power grid. This thesis focuses on vulnerabilities associated with EV charging and the effects of cyberattacks on grid stability and resilience. Of particular interest is the Open Charge Point ...
Exploring the potential of Solid Pods for the cultural sector offers an exciting opportunity to address challenges in data management, privacy, and interoperability. Solid Pods, a technology framework designed to enable individuals to store and control their data, promises transformative applications in the cultural sector. This thesis investigates how Solid Pods can be applied to ...
Conveying information in a tour traditionally either requires a real human or an audio recording. However, the human guide might not always be available and the quality in the tours varies. With audio recordings, extra care has to be taken to convey to the user which element is currently being talked about since there are ...
Learning content by heart can be facilitated by the method of Loci. In this mnemonic technique, the learner converts pieces of information into mental imagery. The imagined representations are then anchored in a location. If the learner then traverses a path through this location, the information can be remembered by recalling the mental imagery. However, ...
The emergence of large language models (LLMs), along with recent advances in mixed reality (MR) and virtual reality (VR), enable new opportunities for applying virtual agents in education. These simulated humans can imitate real-life situations and interactions with native speakers, which leads to an immersive and engaging learning experience. Especially in VR, interactions can be ...
Large Language Models (LLM) can be applied to transform a natural language (NL)-based text input query into a NL-based text answer. A common use case are personal assistants, e.g., for learning activities. In such teaching contexts they can process knowledge recorded in plain text documents, create summarizations, or teach knowledge according to a curriculum. However, ...
This project aims to develop a methodology for the systematic selection and implementation of identifier systems in manufacturing, with a focus on ultrashort-pulsed (UKP) laser systems. By creating a robust identification framework tailored to manufacturing environments, the project will enhance data traceability, interoperability, and reusability within data-driven feedback loops, particularly in highly automated settings. The ...
This master’s thesis builds on the Psychomotor Feedback Engine (PFE) and the IMPECT framework , aiming to improve the graphical user interface that teachers use to implement rules and feedback elements in psychomotor learning.
This thesis aims to address those usability issues by redesigning the teacher interface and integrating the IMPECT framework to ...
This project aims to develop a comprehensive knowledge graph that represents German law documents, including cases and statutes. By creating an ontology tailored to the legal domain and leveraging automated annotation techniques, the project will transform unstructured legal text into structured data that can be queried. This knowledge graph will support legal research, enhance information ...
This thesis investigates the application of federated learning (FL) to the Personal Health Train (PHT) paradigm, exploring how FL can be better adapted to improve privacy-preserving data analysis in healthcare. The research examines how PHT can facilitate secure, distributed machine learning on sensitive medical data across different institutions, while ensuring data privacy and compliance with ...
This research investigates hallucination in vision-language models, focusing on the role of the attention mechanism in contributing to and potentially mitigating hallucinations. The work explores how attention layers influence the integration of visual and textual information and identifies techniques for reducing the generation of inaccurate or irrelevant outputs. A critical research question is understanding how ...
This thesis focuses on designing an Agentic Graph Retrieval-Augmented Generation (RAG) system specifically for question answering in oral maxillofacial surgery (OMS) guidelines. By leveraging graph-based knowledge representation and advanced language models, the system aims to improve accuracy and efficiency in accessing and interpreting surgical guidelines. Key research areas include the integration of graph databases, ontology-based ...
This thesis explores the application of diffusion models for the segmentation of brain tumors in 3D MRI images. By leveraging the robust generative capabilities of diffusion models, the research investigates how these models can accurately identify and segment tumor regions in volumetric MRI data. The study focuses on enhancing tumor detection accuracy and addressing challenges ...
This thesis aims to develop a single-cell-centric biomedical foundation model that leverages the capabilities of generative pre-trained transformers to enhance the analysis of single-cell RNA data. The model will address critical tasks in single-cell biology, such as cell-type annotation, perturbation prediction, identification of pathogenic cells, and gene network inference.
This thesis is co-supervised by Sikander Hayat ...
Mixed reality agents are simulated humans who are displayed in a mixed reality environment, e.g., in augmented reality or virtual reality. They provide the opportunity to support teaching activities with automation. Possible use cases include general presentations in one place, e.g., of lecture content and station-based routes as seen in museums or with tourist guides. ...
We are looking for a highly motivated master student to work on an innovative project for their master’s thesis as soon as possible. The project involves the implementation and evaluation of a programmable money approach utilizing verifiable credentials and zero knowledge proofs.
