Laura Spillner

Laura Spillner is a doctoral researcher at the Digital Media Lab. She studied media science and digital media and then completed a master's degree in computer science at the University of Bremen, with a focus on artificial intelligence, cognition and robotics. Her master's thesis focused on natural language processing and conversational agents.
Laura is working in the European Project "MUHAI: Meaning and understanding in Human-centered artificial intelligence". 
In this project and in her PhD thesis she is researching natural language understanding, and the development of explainable algorithms AI and hybrid AI in the field of language processing.

• Natural language understanding: e.g. instruction parsing, topic modelling, understanding different points of view and political narratives in social media texts
• Evaluating (deep) language understanding: e.g. in comparing machine learning/symbolic AI/hybrid AI
• Visualization for NLU: e.g. interactive topic networks or narrative graphs, visualizing meaning in word embeddings
• Interaction with AI/Robotic agents: e.g. explaining AI predictions or agent behaviour, teaching intelligent agents new knowledge, ...

I currently have open thesis projects in these two general domains (25.11..2024):

• natural language interaction/conversational user interfaces: how do changes in language impact user interaction - e.g. can you use language cues to signify how confident an AI is in its answers? Can AI use humor effectively? How can language be personalized to a user?
• Interaction with AI, explainable AI: if AI is able to explain its reasoning to a user, how does the presentation of the explanation (e.g. natural language vs. graphical, confidence of the AI, etc) influence users' behaviour? How do users interact with AI explanations, how much do they even read them?