Julian Berger

Julian Berger is a postdoctoral researcher at the Max Planck Institute for Human Development in the Center for Adaptive Rationality, where he explores how to enhance decision-making through hybrid human-AI systems. He is also a fellow of the Joachim Herz Foundation and has received funding from the Foundation of German Business and the Danish Data Science Academy.

• Education:
  • M.A. Psychology in Business and Economics, Universidade Catolica Portuguesa (2021)
  • B.A. Politics, Administration and International Relations, Zeppelin Universität (2018)

His research spans human-AI collaboration, collective intelligence, and interpretable machine learning. A recurring theme in his work is developing methods to combine human expertise with AI capabilities for accuracy in domains like medical diagnostics, credit scoring, and football analytics. He has authored publications in high-impact venues such as PNAS, Nature Human Behavior, and Science and Medicine in Football.

Scientific awards and funding include:

• Fellowship for interdisciplinary economics, Joachim Herz Foundation (2024)
• PhD funding from the Foundation of German Business (Stiftung der deutschen Wirtschaft)
• Research grant from the Danish Data Science Academy

His recent article trends emphasize ensembling techniques that leverage complementary human and AI errors, algorithmic fairness, and practical heuristics like Hybrid Confirmation Trees. These works demonstrate significant improvements in diagnostic accuracy and decision cost-efficiency.

Beyond academia, Berger works as a consultant and ML engineer with Simply Rational, focusing on interpretable models for financial and sports analytics. His work bridges theoretical research with real-world applications, prioritizing fairness, transparency, and human accountability in AI systems.