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Information about Diploma/Master thesis process

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  • ScrumiX: AI-empowered agile project management system


    As software engineering continues to evolve, agile frameworks have become the main paradigm for project management and development. Among these, Scrum is widely adopted by numerous software organizations due to its iterative and incremental development approach, emphasis on team collaboration, and rapid feedback cycles. With the ongoing advancements in artificial intelligence technologies, particularly the recent ...
  • LLM-Powered Virtual Reality Agents as Technical Support


    Technical support is an essential aspect of various industries, e.g., to provide help with maintaining machinery and IT systems. However, diagnosing error messages and faults in complex technologies can be a time-consuming and challenging task. The maintainer has to search through the long documentation booklets for the technology in order to find a solution or ...
  • Enhancing Mixed Reality Instructional Agents with Large Language Models


    The innovative integration of Mixed Reality and Large Language Models can lead to highly interactive instructional MR agents. Utilized as automated instructors, these MR agents have the potential to significantly enhance traditional instruction manuals by providing visual guidance. For instance, they can illustrate the next required actions in practical tasks such as tightening screws in ...
  • Developing a Benchmark Environment to Evaluate IntrusionDetection Systems in the Context of Industrial Control Systems


    The increasing connectivity of Industrial Control Systems (ICS) has elevated the need for robust cybersecurity measures. However, evaluating the effectiveness of Intrusion Detection Systems (IDS) in ICS environments remains fragmented and inconsistent. This thesis addresses this challenge by developing a systematic, modular benchmarking environment that enables reproducible and standardized evaluation of machine learning-based IDS across ...
  • SMART-LLM: Sensor-based Maintenance bot for Analysis and Retrieval of Time Series data using LLMs


    The goal of this thesis is to design, implement, and evaluate a sensor-based maintenance bot that uses Large Language Models (LLMs) to support predictive maintenance and decision-making. The bot should be capable of retrieving, analyzing, and reasoning over time series sensor data as well as unstructured maintenance-related documentation (e.g., technical manuals, incident reports). The result ...

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