SynoSys, along with a consortium of leading researchers, has secured funding for the DREAM EP (Data-informed Responsive Epidemic Analysis and Multiscale-Modelling for Epidemic Preparedness) research project in pandemic forecasting.

A major milestone for SynoSys: We have been awarded €2.3 million in funding from the Federal Ministry of Health (BMG) for the SynoSys.PC project, aimed at advancing the understanding of Long-COVID and advancing patient care.

We perform comprehensive spatiotemporal analyses of sleep patterns in a sample of over 100,000 individuals across Germany spanning almost 3 years. As part of the Robert Koch Institute's Data Donation Project for the early detection of COVID-19, sleep data was collected in a privacy-preserving fashion by passive sensors in consumer wearable devices.

Understanding how network structures interact with the evolution of competing lineages in clonal populations.

Machine learning-based COVID-19 detection using wearable sensor data such as resting heart rate, sleep duration, and step count, leveraging interpretable catch22 features and logistic regression models.

FEDORA - Federated Network Modeling of Ecological Complex Dynamical Patterns in Post-COVID aims to advance the understanding of how ecological systems are affected by complex dynamical patterns emerging in the aftermath of the COVID-19 pandemic.