Unai Fischer Abaigar

Research Interests

• Algorithmic Decision-Making
• (Causal) Machine Learning for Resource Allocation
• AI in Public Policy and Public Administration

Short Description

Unai is a PhD student in Statistics at the University of Munich (LMU), where he studies the foundations of prediction systems used to guide resource allocations in the public sector. A core theme of his research is taking a holistic view of decision-making systems, examining not only the predictive algorithms themselves but also how they are designed, deployed, and integrated into broader decision-making processes.

He joined the Social Data Science and AI Lab in October 2022, supported by the Konrad Zuse School for Excellence in Reliable AI and the Munich Center for Machine Learning. He is advised by Christoph Kern and Frauke Kreuter.

In Fall 2024, he was a visiting fellow at Harvard, hosted by Cynthia Dwork and Juan Carlos Perdomo.

He holds a BSc and MSc in Physics from Heidelberg University, where he specialized in dynamical systems, networks, and statistical machine learning for time series. Before starting his PhD, he worked as a research associate at the Hertie School Data Science Lab in Berlin, exploring machine learning applications in public policy and governance.