Ulf Aslak

PhD student / physicist / data scientist


I am a PhD student at the Centre for Social Data Science, University of Copenhagen, a visiting researcher at the Technical University of Denmark (DTU) and an external lecturer at DIS Copenhagen. I hold degrees in Digital Media Engineering (M.Sc.) and Physics (B.Sc.) from DTU, am a former visiting researcher at the Uri Alon lab at the Weizmann Institute of Science, and a former Data Scientist at Trustpilot. I won the inaugural Data Stories competition by Science Magazine (submission). Areas of expertise are network science, machine learning, and data visualization.


My research digs into various aspects of human behavior using computational methods. I work with data from the Copenhagen Networks Study under supervision of Sune Lehmann. My interests point in many directions, but the central theme is that I want to discover fundamental principles that govern social interactions, and build theoretical and practical tools that allow us to better approach questions in the social sciences. My most recent work presents a method for clustering dynamic networks that span long periods of time. By applying it to real-world networks that map face-to-face interactions in time it offers novel insight into how humans meet in groups. In my current work, I investigate how this couples to human mobility. Conventional research proposes human travel to be scale-free. Using a dataset that, outside of industry, is unparalleled in size and resolution we work to show that human travel is in fact hierarchical and that there are multiple disjoint scales at which humans transition between places, and that these transitions are highly predictable given knowledge about a persons social state.

Interactive visualisation of social community dynamics in temporal face-to-face networks (view on desktop). Uses method from this paper. This visualization won the Data Stories competition by Science Magazine in 2016.