Chatbot

A key challenge in designing conversational user interfaces is to make the conversation between the user and the system feel natural …

Mental health issues, such as depression, are a large-scale problem with significant individual and socioeconomic costs. Yet, people often do not seek or receive treatment. Together with our colleagues from University of Greifswald, we design and evalute mental health chatbots and investigate how their personalization can contribute to treatment success.

Dashboards have become popular tools for visualizing, exploring, and analyzing data in business and society (e.g., COVID-19 dashboards). However, less tech-savvy users often struggle to find and extract the information they need. In our research, we address this problem by extending dashboards with a conversational user interface so that users can interact with a dashboard using natural language.

Chatbots often reach their limits in interactions with customers. However, since analyzing customer-chatbot interaction data is difficult and labor-intensive, existing limitations are not immediately apparent to both chatbot operators (e.g., customer service managers) and chatbot developers. Our research aims to address this challenge by developing novel chatbot analytics systems that can generate valuable insights for managers and developers.

Emotion-aware chatbots that can sense human emotions are becoming increasingly prevalent. In our research, we study how these chatbots can support team communication on collaboration platforms such as Slack and Microsoft Teams.

Developing chatbots is often more difficult and expensive than expected. In addition, domain experts and users are not (or only partially) involved in the development process. Our research tackles this challenge by developing interactive systems that support chatbot developers to build better chatbots.