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Department of Computer Science
[Translate to English:] © Oliver Schaper​/​TU Dortmund
Enterprise Computing

Current Topics for Theses

The possibility of writing a Bachelor's or Master's thesis is explicitly not limited to the following topics. These merely give an indication of the range of topics.

Topic overview

  • Degrees of automation of Intelligent Process Automation: Intelligent systems are used in a spectrum of degrees of automation - from Robotic Process Automation to Autonomous Agents - depending on the process complexity and the use of AI. (Seyyid A. Ciftci)
  • Development of a BPM Lab: Installation of BPM systems, implementation of demo processes, documentation (Prof. Christian Janiesch).
  • Development ofa process mining lab: Installation of process mining systems, implementation of demo processes, documentation (Prof. Christian Janiesch).
  • Development ofan RPA lab: Installation of RPA systems, implementation of demo bots, documentation (Prof. Christian Janiesch).
  • Artificial intelligence in Industry 4.0: The application potential of artificial intelligence for optimizing operational production is broadly diversified, and practical implementations are constantly increasing, e.g. in robotics, process automation or machine communication. (Philip Stahmann)
  • Implementation of RPA: Modeling and automation of a BPMN model to optimize human-machine interaction. (Seyyid A. Ciftci)
  • Management of RPA: Practical relevance, economic efficiency, selection decision, implementation, maturity models, success stories and technological debts of RPA. (Prof. Christian Janiesch)
  • Process patterns for the interaction of decision makers in Industry 5.0: Investigation of an effective and collaborative interaction between decision makers and AI assistants in Industry 5.0 to develop human-centered and sustainable solutions. (Maximilian Nebel)
  • Advanced analytics in a socio-technical context: Effects of predictive and prescriptive analysis results on the cognition and emotions of users of information systems can provide insights into the acceptance and diffusion of information systems. (Philip Stahmann)
  • AI Mindfulness, Human-AI Interaction and Hybrid Intelligence: People have to interact with AI systems in many places. This may require new processes and forms or patterns of collaboration. (Prof. Christian Janiesch, Pauline Speckmann)
  • Interaction system development: Human-machine interaction plays an increasing role in IIoT, and to ensure productive work, cognitive load must be minimized, among other things. The aim of the work is the formulation of design criteria and the prototypical creation of such a system for decision-makers in the context of IIoT, taking cognitive load into account. (Maximilian Nebel)
  • Biases in machine learning: Machine learning is almost always based on data created by humans. This means that this data is subjective and the learned knowledge of the "artificial intelligence" is biased. (Pauline Speckmann)
  • Explainable AI: Processing and working with the most common XAI techniques and XAI tools. If necessary, implementation of visual components for new use cases such as process management. (Pauline Speckmann)
  • Explainability in DSS/RS: How can the mechanics and decisions of Decision Support Systems (DSS) and Recommender Systems (RS) be made explainable to their users? (Pauline Speckmann)
  • Application potential of AI for applicant management: Developments towards an employee market due to the shortage of skilled workers mean that employers must optimize their applicant management. Artificial intelligence methods should also be used for this purpose. (Maximilian Nebel)
  • Implementation of autonomous agents: AI-supported agents enable autonomous, efficient decisions in complex processes that react flexibly to dynamic changes and requirements. (Seyyid A. Ciftci)
  • Realization of Trustworthy AI: Development and instantiation of design principles for AI software that gains, maintains or calibrates the trust of users. Trust can and should be considered multidimensionally, for example, trust in cyber security and data protection, trust in algorithmic decisions and trust in software providers can be distinguished. (Alexander van der Staay)
  • Algorithmic Supply Chain: Development of solutions for the "many hands problem" in algorithmic supply chains with a special focus on AI cloud services (AI-as-a-Service). (Alexander van der Staay)
  • Algorithmic Accountability: Development of methods and frameworks that ensure transparency, traceability and ethical standards in the development and application of algorithmic systems. (Alexander van der Staay)
  • Resource-conserving AI in operational applications: Development of operationally feasible design principles or solutions that minimize the energy consumption and environmental impact of AI. For example, through the use of ML-optimized computing units such as TPUs. (Alexander van der Staay)
  • A Maturity Model for the development from Industry 4.0 to Industry 5.0: Development of a maturity model that analyzes and supports the transition from Industry 4.0 to Industry 5.0 in a structured way. (Maximilian Nebel)
  • Learning Classifier Systems (LCS): LCS are able to classify data on the basis of evolutionary algorithms. This results in potential for real-time classification, e.g. for anomaly detection. (Philip Stahmann)
  • Potential uses of affective computing for the real-time support of decision-makers: Investigation of how affective computing can support decision-makers in recognizing early signs of stress, for example, in order to improve their cognitive state. (Maximilian Nebel)

Theses can also be written in cooperation with Queenland University of Technology (QUT) in Brisbane, Australia. Thesis topics will be agreed upon between the candidate, Prof. Rosemann and Prof. Janiesch and will focus on the "algorithmic" or "trusted enterprise", emphasizing the interface between computer science and management, especially in the areas of digitalization and artificial intelligence. If interested, please contact Prof. Janiesch directly outside the usual thesis application cycle.

Theses can also be written in cooperation with the Stevens Institute of Technology in Hoboken, NJ, USA with a view of downtown New York City . Thesis topics will be agreed upon between the candidate, Prof. zur Mühlen and Prof. Janiesch and will focus on the "business process management" and "process modeling". If interested, please contact Prof. Janiesch directly outside the usual thesis application cycle.

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