Thesis projects

We are always interested in meeting passionate students. Please, explore the research focus of our chair and the research areas of our staff to see where your interests align. Your own thesis proposals are highly encouraged. For enquiries or to suggest a topic, please contact the member of staff in the relevant area. Additionally, you can find a list of topics below that are currently open for thesis projects. For more information on a specific topic please contact the relevant person. Please always include your CV and transcripts with your request.

• [BSc/MSc] Open Topics in Time Series Analysis, AutoML, and Uncertainty Quantification
  

  Time series data is ubiquitous in many domains, including finance, healthcare, and IoT. However, extracting representations from time series data is challenging due to its high dimensionality and temporal dependencies. Additionally, quantifying uncertainty associated with time series data is difficult due to its unique characteristics. We are seeking motivated students to work on topics related to time series analysis (with a focus on representation learning), AutoML, and uncertainty quantification. The goal is to develop novel methods and techniques that advance representation learning and uncertainty quantification for time series data, addressing gaps in the current state of the art.

  Potential research directions include, but are not limited to:

  • Investigating and benchmarking uncertainty quantification methods for time series models
  • Studying transfer learning and domain adaptation methods for time series applications
  • Exploring conformal prediction and conformalised prediction sets for reliable uncertainty estimation in time series-related tasks
  • Developing AutoML frameworks for automated selection and optimisation of uncertainty quantification or conformal prediction methods in time series analysis

  The exact thesis topic will be finalised through discussion between the student and the supervisor, based on the student's interests and experience. If you are interested or have any questions, please contact the supervisor, Wadie Skaf (see below).

  When applying, please include the following documents:

  • CV
  • Transcripts for all completed and ongoing degrees (undergraduate and postgraduate)
  • A brief motivation letter (1 page max) that addresses the following questions:
    • Why are you interested in this topic?
    • Which specific sub-topic(s) would you like to work on?
    • What experience and skills do you have that are relevant to your chosen sub-topic(s)?

  Please note: Incomplete applications will not be considered. Only shortlisted candidates will be contacted.

  Contact: skaf[at]aim[dot]rwth-aachen[dot]de