Unai Fischer Abaigar

Research Interests

• Reliable Machine Learning for Decision-Making

• Distribution Shifts

• Causal Machine Learning

• Uncertainty Estimation

• AI and Public Policy

Short Description

Unai joined the SODA chair as a PhD Student in October 2022. He is supported by the Konrad Zuse School for Excellence in Reliable AI and the Munich Machine Learning Center. His research is centered on the development of reliable AI systems for facilitating high-stakes decision-making in real-world applications, with a primary focus on distribution shifts and causal estimation. He is very interested in the societal implications of employing algorithmic decision-making within the public sector.

Unai studied Physics at the Ruprecht-Karls-Universität Heidelberg, focusing on dynamical systems, networks, and statistical machine learning for time series. Following his graduation, he spent some time working as a research associate at the Hertie School Data Science Lab in Berlin, exploring future avenues for applying machine learning methods to problems from public policy and governance.