Master-Thesis (m/f/d): Computational Human Computer Interaction

We are driven by designing and implementing user-centric systems, that consider the unique challenges and implications of human computer interactions while driving. A promising path to understanding user’s needs is through analyzing and understanding the environment they are exposed to while driving. Exploring this dynamic context provides valuable insights for tailoring interactions that enhance user experience and safety on the road. This Master’s Thesis aims at using state of the art machine learning methodologies to encode, and understand such context variables and enable novel applications. By delving into advanced techniques, we seek to create intelligent systems that seamlessly integrate with the driving environment, ultimately improving the overall usability and effectiveness of incar interactions. 

Tasks:

• research the state of the art in context understanding
• develop and implement a contextaware system that enables a novel interaction paradigm
• evaluate the system in a quantitative or qualitative in-the-wild study 

• Studies in Computer Science or similiar, ideally with a focus on Artificial Intelligence and/or Human Computer Interaction 
• very good programming skills in Python
• very good knowledge about user studies and statistical testing
• good knowledge about state of the art Machine Learning methodologies
• fluent in English (oral and written) 
• Previous scientific publications are a bonus 

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