Prof. Dr. Stefan Decker - Theses
Bachelor, Master
Entwicklung einer Co-Simulationsumgebung zur Abbildung des Prozessdatenverkehrs von intelligenten Energienetzen - Open
Supervised by Prof. Dr. Stefan Decker, Dr-Ing. Michael Andres
Bachelor, Master
Entwicklung eines Bilderkennungsverfahrens auf Basis neuronaler Netze zur Identifikation elektrischer Anlagen - Open
Supervised by Prof. Dr. Stefan Decker, Dr.-Ing. Michael Andres
Bachelor, Master
Entwicklung eines Systems zur Angriffserkennung in intelligenten Energienetzen - Open
Supervised by Prof. Dr. Stefan Decker, Dr-Ing. Michael Andres
Master
Exploring Unknown Environments - Finding Pollution in Underground Pipes - Open
Supervised by Prof. Dr.-Ing. Gerd Ascheid, Prof. Dr. Stefan Decker; Advisor(s):
Dr. Michael Cochez,
Ahmed Hallawa
Master
Investigating Replay Methods for Institutional Incremental Learning - Open
Supervised by Prof. Dr. Stefan Decker; Advisor(s):
Sascha Martin Welten, M.Sc.,
Yongli Mou
Bachelor, Master
Knowledge-based Bot Configurator - Open
Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Stefan Decker; Advisor(s):
Alexander Tobias Neumann, M.Sc.
Whether it's customer support, surveys or a simple chatbot, there's no need to reinvent the wheel. Creating bots should be easy. This thesis will implement a configurator for (chat)bots by utilizing the social bot framework and bot blueprints. The result of the thesis should be a template library offering different social bot types (e.g. chatbots, crawlers, transactional bots or informational bots) that can be configured.
Bachelor, Master
Ontologies and Model-Driven Software Engineering of Information Systems - Open
Supervised by Prof. Dr. Bernhard Rumpe, Prof. Dr. Stefan Decker; Advisor(s):
Malte Heithoff (SE RWTH),
Johannes Theissen-Lipp
Bachelor, Master
Privacy-Preserving Machine Learning - various thesis opportunities - Open
Supervised by Prof. Dr. Stefan Decker; Advisor(s):
Mehdi Akbari Gurabi, M.Sc.
Bachelor, Master
Master
A Blockchain Enabled Fast Consensus Mechanism in Federal Learning - Running
Supervised by Prof. Dr. Stefan Decker; Advisor(s):
Dr. Oya Deniz Beyan,
Yongli Mou,
Fengyang Guo
Bachelor, Master
A Cognitive Modeling-Based Architecture for Realistic Agents in Mixed Reality - Running
Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Stefan Decker; Advisor(s):
Benedikt Hensen, M.Sc.
Courses in higher education, e.g. at universities, face a challenge regarding scalability. Ideally, every student should be able to contact a mentor to benefit from the mentor’s experience and to reach the learning goals. However, if the number of participants in a course rises, the limited resources of the institution are quickly exhausted. This leads to a high workload for academic staff and decreases the mentoring quality since there is less time for mentors to address the individual needs of the students. A solution to this problem is socio-technical support for mentoring processes which combines social processes like peer mentoring and technological processes, e.g. for student’s feedback. As a result, text-based chat bots were created which can answer student’s questions and give feedback about exercises. We would now like to enhance the interaction with such bots by upgrading them to Mixed Reality agents. Such agents are shown as an avatar in a Mixed Reality environment and can interact with virtual content, users and other bots. They form a natural user interface where students can talk to the agent to get advice and it can also make autonomous decisions to guide the learning process. If the agent cannot answer a question, it can call a human mentor to join the conversation. This system considerably lowers the workload of the mentors while improving the mentoring experience of the students.
Bachelor
A Conceptual Framework Towards Application-specific Presentation Views on Knowledge Organization Systems - Running
Supervised by Prof. Dr. Stefan Decker; Advisor(s):
Dr. Oya Deniz Beyan,
Heiner Oberkampf,
Jan Winkelmann
Bachelor, Master
A containerisation pipeline for distributed analytics algorithms: The algorithm assembly line - Running
Supervised by Prof. Dr. Stefan Decker; Advisor(s):
Sascha Martin Welten, M.Sc.,
Dr. Oya Deniz Beyan
Bachelor
A Mixed Reality-Based Card Game for Formal and Informal Education - Running
Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Stefan Decker; Advisor(s):
Benedikt Hensen, M.Sc.
A challenge of existing educational Mixed Reality applications concerns the difficult accessibility of technology for students. Many applications require expensive head-mounted displays or high-end smartphones which can only be tried by students at the university for a limited amount of time. However, Mixed Reality content can also be shown on a broader range of devices using marker-based technology. Here, a marker is used as an anchor to show a 3D model above it. If the marker is filmed by a smartphone, it can calculate the view angle and render the 3D model from the same perspective. A challenge of marker-based applications is to find a meaningful integration of the markers into the environment. The markers should be easily recognizable but also need to give the user an idea about the 3D model that they can show.
Bachelor
A Social Bot Success Model - Running
Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Stefan Decker; Advisor(s):
Alexander Tobias Neumann, M.Sc.
Social Bots (software robots) are computer algorithms that automatically produce content and interact with humans on social media. The goal of this study is to discover success factors that make the use of a (chat)bot successful.
Open Access to MIT Press Book „Metamodeling for Method Engineering” 