Completed Theses
The immense growth of scientific literature makes it nearly impossible for researchers to keep pace with all new developments in their domains. An automated scientific Question Answering (QA) system could substantially expedite the process of literature review, hypothesis generation, and knowledge extraction. With the emergence of Large Language Models (LLMs) like GPT, BERT, and their ...
In recent years, the advancements in natural language processing and machine learning have revolutionized various industries and domains.
This thesis aims to explore the potential of training a Large Language Model (LLM) on Git source code repositories to enable it to effectively respond to queries regarding the codebase, such as dependencies and functionality.
Analysing Policy Documents Using AI
Analysing Scientific Publications Using AI
Adding a Beacon functionality to the Personal Health Train
Detect Flames in industrial Video data using edge devices.
Data-driven quality assurance in grinding manufacturing technology
Adaptive Operator Placement for Edge Clusters using Cluster Simulation
User-defined and Predictive Quality of Service Monitoring for on-the-edge Data Stream Processing
This thesis focuses on integrating a Moodle chatbot into online courses using advanced Natural Language Processing techniques. The chatbot will provide educational and organizational support to students, and its performance will be evaluated through technical analysis and user feedback.
MuCo - Music Composer: Can AI Rival Human Creativity?
This thesis topic would involve researching and developing a recommender system, integrated with Large Language Models (LLMs), that can take into account users’ diverse skills and certifications, and provide personalized course recommendations that align with their career goals and interests. The thesis could explore different machine learning algorithms and data processing techniques to optimize the ...
The Implementation of Federated Learning for a Data Space in the Plastic Packaging Industry
This thesis aims to develop a framework for analyzing chatbot conversations using process mining techniques. The framework will allow users to discover process models from chatbot event logs, compare them to the bot models, and enhance them based on the analysis results.
Effects of Generative Replay-based methods on Catastrophic Forgetting in DA on healthcare data
From Simulation to Real Settings: Investigating the Testability of Distributed Analytics Experiments
Establishing Trust in P2P Distributed Analytics Infrastructures
This thesis aims to explore Deep Reinforcement Learning based methods for strategy optimization in the Contract Bridge game, such as Multi-agent Reinforcement Learning, Value-based Learning, and Policy-based Learning, as well as Knowledge Representation and Reasoning based methods such as Multi-agent Epistemic Situation Calculus
Adversarial Attacks against Face Detection Systems
Improved Bottom-up Deep Learning Approach for Neuronal Cell Instance Segmentation
Edge computing offers a framework for offloading the computational effort required by IoT applications.However, privacy issues and cost constraints for cloud infrastructures pose substantial difficulties to IoT service deployment. We wish to look at the possibilities of Peer-to-Peer networks and WebAssembly for IoT task offloading. As a result, a comparison of existing offloading tactics and ...
The aim of this thesis is to build a MLOps-based system to compare the variations in the motions executed while performing various sports-related movements. In essence, we are interested in comparing movements across multiple sensor-suit based recording sessions.
Politicians are highly public individuals. A lot of data on them is available online. Many try to use social media such as Twitter to express their views, support other members of their party or interest groups, and interact with the public. Some also use it to branch out and connect to other countries’ politicians or ...
