Knowledge Discovery Group

The mission of the Knowledge Discovery group is to extract the maximum value out of data. To that end, we follow a data-driven approach, which is domain-agnostic in its application. Our research is related to the scientific fields of machine learning, natural language processing and information retrieval. Methods from these fields form the algorithmic base of data science, artificial intelligence and interactive applications.

Contact: Roman Kern (

Motivational Media Technologies Group (MMTG)

The MMT Group focuses on research and development of tools, applications and approaches to support and improve knowledge transfer, learning and training, as well as health and well-being. Research interest includes modern e-learning and e-assessment applications, game engineering, immersive environments and mobile setups as well as natural language processing, social media technologies and learner and gamer analytics. Read more »

Contact: Christian Gütl ( and Johanna Pirker (

Social Computing

We research computational models and algorithms to understand and shape human activities and social phenomena in complex systems such as the Web. We work on topics like adaptive and personalized recommender systems; modeling social dynamics in online collaboration systems and exploring reasons underlying biases in algorithms and data. We are open science advocates and we research on discovery and accessibility of research artefacts and altmetrics. Via policy making on European level, we contribute to a responsible assessment of scholarly impact.

Contact: Elisabeth Lex (

Web Science and Engineering

We work on machine learning for the analysis of big information spaces and sensor data, as well as social network theory and semantic technologies. Our aim is to use and combine these intelligent methods and as a result to create hybrid helpers that complement the cognitive abilities of humans.

Contact: Denis Helic (

Workplace Learning and Data-Driven Business

We understand, design and evaluate socio-technical interventions in organisations, which means that we study technology together with the way of using it in an organisational context. Our research focus is on learning in organisations at all organisational levels, knowledge sharing and protection, decision making, and identifying data-driven business model opportunities.

Contact: Viktoria Pammer-Schindler ( and Stefan Thalmann (