Katharina Ledebur

Katharina Ledebur is a Postdoctoral Fellow at the Complexity Science Hub (CSH) in Vienna, Austria, where she conducts research at the intersection of computational modeling, epidemiology, and public health. She also completed her PhD jointly at the Complexity Science Hub and the Medical University of Vienna in March 2025, indicating a strong affiliation with both institutions.

Education:

• Bachelor’s and Master’s in Biophysics, Humboldt University of Berlin
• PhD in Computational Epidemiology / Health Sciences, Complexity Science Hub & Medical University of Vienna (2025)

Her research focuses on modeling the causes and consequences of diseases, particularly examining how environmental and societal factors influence health outcomes. Key interests include the impact of climate change on morbidity, chronic disease dynamics in aging populations, and infectious disease modeling. She applies advanced computational techniques such as agent-based modeling and network analysis to large-scale health datasets and wearable data.

Her recent publications reveal a consistent trend in leveraging real-world data—ranging from hospital records to smartwatch measurements—to understand disease patterns, evaluate public health interventions, and forecast healthcare system impacts during pandemics. Her work often integrates meteorological, behavioral, and biological data to improve predictive accuracy in epidemiological models.

While no formal scientific awards are listed, her contributions to high-impact journals such as PLoS Computational Biology and Journal of the Royal Society Interface reflect strong scholarly recognition.

Katharina actively contributes to interdisciplinary research projects including HeatProtect (climate and health), ASCII (supply chain intelligence), and D4Dairy (digital agriculture and health). She advises no students currently, and no grant leadership is mentioned, but she is a key collaborator in data-driven health initiatives. Her work on passive sensing and long COVID has received press attention, highlighting its societal relevance.

She is involved in research teams focused on digital epidemiology and complex systems in healthcare, working closely with leading scientists like Peter Klimek and Stefan Thurner. These teams emphasize open science, data privacy, and translational modeling for policy impact.