Michael has been a Visiting Student at the Complexity Science Hub since March 2025.

Coming from a background in theoretical computer science, Michael is particularly interested in how algorithmic methods and the theory of networks can be applied to understand complex social and organizational systems. His research at CSH focuses on reconstructing organizational information networks by analyzing online article reading patterns across millions of firms. Working on this project with Eddie Lee, he explores how information spreads within organizations, developing novel methods to infer organizational structures from their information consumption behaviors.

Michael holds a Bachelor’s in Computer Science at TU Wien, where he is now completing his Master’s in Logic and Computation. There, he specialized in algorithms and graph theory – the mathematical foundations for analyzing complex networks.

He is also pursuing a complementary Master’s in Epistemologies of Science and Technology at the University of Vienna, extending his technical foundation with insights from history, philosophy, and sociology to better understand the systemic impacts of technology on society.