Fiona Sauerbier

Fiona Sauerbier serves as a Scientific Associate at the Institute for Logistics, Transport and Production within the University of Hamburg Business School. Her research focuses on choice-based optimization under high-dimensional systems, directly contributing to advancements in logistics, transport, and production management through computational modeling and data-driven solutions.

Her educational background includes a Master of Science degree. Core research interests encompass Logistics, Transport, Production, Optimization, Machine Learning, Crowd Management, and Traffic Analysis. She develops sophisticated frameworks for resource allocation in complex systems, particularly addressing crowd dynamics and transportation networks during large-scale international events.

Recent publications reveal a strong trajectory in applying machine learning to real-time traffic forecasting for mega-events like the FIFA World Cup, while simultaneously advancing theoretical foundations of choice-based optimization in high-dimensional spaces. This dual focus bridges practical event logistics challenges with rigorous mathematical modeling.

She operates within the research team led by Univ.-Prof. Dr. habil. Knut Haase, collaborating on projects that integrate optimization theory with transportation engineering applications. Her office is located at Moorweidenstraße 18, Room 2027 in Hamburg, with appointments conducted via email contact.