Studying the hidden patterns of social systems through networks, data, and complexity science.
My work focuses on developing a quantitative understanding of social systems based on massive datasets. Trained as a physicist, I use methods from complex systems, machine learning, and statistics to make sense of human behavior at scale.
With Laura Alessandretti, I direct the Social Complexity Lab, where we study everything from how people move through cities to how information spreads through networks.
I am a member of the Danish Royal Academy of Sciences and Letters. During the COVID-19 pandemic, I served on a Danish government task force modeling disease spread, and contributed to the development of the national contact tracing app.
I have published 112 papers, including work in Nature, Nature Physics, Science Advances, PNAS, and Nature Human Behaviour.
Community detection, temporal networks, and the structure of large-scale social systems.
How people move through cities and across borders, and what mobility patterns reveal about society.
Applying physics and machine learning to understand behavior, sleep, academic performance, and health.
How ideas, news, and misinformation propagate through social media and communication networks.
Modeling disease transmission dynamics using network science and large-scale behavioral data.
Quantitative analysis of online behavior, platform effects, and digital social systems.
Networks are at the heart of my research. Drag the nodes below to explore a force-directed graph — a model of how connected systems self-organize.
I teach courses on social data analysis and network science. Materials are open on GitHub.