Central European University (CEU) in Vienna is a global hub for research and learning, blending American and European academic traditions. Its Department of Network and Data Science is the only department of its kind in Europe, with a focus on fundamental research in network science, as well as high-impact topics of data science such as artificial intelligence, political polarization, financial markets, socioeconomic inequalities, urban mobility, and migration.

Digital Twin Solutions for Society

With AI rapidly shaping today’s world, CEU faculty are advancing research examining how AI technology can mitigate crises by improving the efficiency and livability for humans in cities. Assistant Professor Jascha Gruebel’s research on digital twins as AI infrastructure focuses on advancing the reproducibility of scientific work, thereby making data more relevant for policymaking.

“While AI-driven scientific discovery in natural sciences already uses AI methods to explore the space of possible hypotheses with regards to a specific research question, we still need to work out how to use these tools in social sciences,” said Gruebel, whose recent publications lay a foundation for advancing implementations of integrated AI-driven digital twin solutions in areas such as sustainable mobility systems, preventive healthcare and animal wellbeing.

Unlocking the Black Box of AI

Head of Department, Professor Marton Karsai and Professor Janos Kertesz are also engaged in research at the intersection of AI and social science, examining the wave of machine-learning-based AI technologies. While a centralized approach to machine learning entails collecting data through opaque “black boxes,” this project explores how the next wave of machine learning and AI tools can be more human-centric, explainable, and decentralized, in line with societal and ethical expectations for trustworthy AI. In another line of research, Professor Karsai and his team study how remotely sensed open data sources can be used to infer high resolution poverty maps with AI tools in developing countries. This research aims to supplement official data sources in countries where poverty mapping is difficult yet crucial for better interventions serving disadvantaged populations. Study With Leading Researchers at CEU When it comes to the integration of research and learning at CEU, Karsai said: “Our students in our Social Data Science Master’s and Network Science PhD programs not only obtain strong methodological foundations in network and data science but also apply these skills directly on

socially relevant problems through coursework and thesis projects in collaboration with our faculty. They develop novel data-driven approaches to study some of the most pressing challenges shaping our increasingly data-driven societies,” said Karsai.

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