Nadine Berner
Nadine Berner 

About me

Research Data Scientist developing analysis methods to gain better understanding of complex system dynamics under uncertainty

 

Board member of the Working Group on Physics, Modern IT and Artificial Intelligence, German Physical Society

I am a research data scientist working in the field of computational statistics and probabilistic modelling of complex systems at the non-profit technical safety organisation Gesellschaft für Anlagen- und Reaktorsicherheit (GRS) in Garching near Munich. Previously, I did my PhD in theoretical physics on Bayesian approaches for the investigation of complex climate time series at the Focus Area for the Dynamics of Complex Systems (DYCOS) and at the Paleoclimate Dynamics Group, both based at the University of Potsdam.

 

Even though the scientific disciplines - complex natural systems and complex engineered systems -  are very different, my research focuses on the general understanding of stochastic transition patterns occuring and influencing all kinds of complex systems. The mutual challenge thereby may be a strikingly simple question: How can I formulate a scientific hypothesis in terms of a probabilistic approach to unravel principles guiding a complex dynamic system? Or in more elegant and ambitious words:

 

"If the universe is the answer, what is the question?"

L.M. Lederman

 

From one perspective I approach this challenge by designing generic probablistic models to analyse observations of natural systems, such as the climate system. The aim is to derive statistical information that helps to decipher the recorded system evolution, e.g. paleoclimate proxy records. From another perspective I approach this challenge by performing ensembles of simulations traversing specific trajectories in the phase space to analyse the behavior of engineered complex dynamic systems in the presence of stochastic transition scenarios. For instance, an important study case is the behavior of a nuclear power plant given failure scenarios assigned with uncertainty. For details, please see my publications.

 

Common to all these approaches is the demand of high performance scientific computing and programing concepts. Therefore, I am additionally interested in information theoretical principles to implement sustainable and platform-independent (mainly pythonic) programs that are in general designed to be performed in multi-core environments.

 

! Upcoming Workshops !

 

06/2021

Summer School on Trends, Rythms and Events in the Earth's Climate System - Past, Present and Future

I am looking forward beeing a lecturer of the one week Module 3 on Uncertainty of Climate Data Across Scales (6-13 June 2021) in this summer school. The interdisciplinary online summer school will be designed for doctoral students, aiming

  1. to improve their skills to understand the complex interaction of the processes in the Earth's climate system,
  2. to acquire knowledge in state-of-the-art methods of time series analysis,
  3. to interpret the results of their analysis of past, present and future climate change, including associated uncertainties, as well as
  4. to identify, predict and communicate the impacts of natural and human-caused climate change in an interdisciplinary and intercultural environment,

taught by a team of experienced lecturers and researchers.