The aim of the research program is to unite and combine current trends in dynamical systems and time series analysis for solving problems in physiology which are governed by repeating processes. Examples are circadian rhythms, cardio-dynamics, sleep processes, glucose-insulin regulation and many others. The importance of the circadian clock to human health was recognized by the 2017 Nobel prize in medicine. The invited participants are experts in mathematics, physics and computer sciences working in applications of dynamical systems and time series in physiology, biology and medicine. The program will explore the state-of the-art mathematics underlying periodic and periodic-like processes in human physiology.

The retreat will focus on models based on deterministic and stochastic differential equations and delay differential equations, dynamical system approaches to time series, statistical mechanics, phase transitions and mean field approaches. The mathematical models of regulatory processes are often informed by data-driven models, derived from spectral analysis and signal processing. Furthermore, the large number of parameters can be difficult to measure. Machine learning and statistical approaches will be explored to estimate parameters. The models are based on real data measured from humans (ECG, EEG, actigraphy, eye movements, glucose levels, insulin sensitivity), and the processes for building models from such data will be discussed.

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