Emerging Fields

The Emerging Fields are devoted to pioneering interdisciplinary research in new fields including the social sciences and humanities. The following list displays the research projects presently running in the five Emerging Fields. Successfully completed projects can be found on the subsequent websites of the individual Emerging Fields.

Projects marked with an asterisk (*) are short-term one-year pilot projects.

Extracting Dynamical Laws from Complex Data (EF1)
Scientists in Charge: Klaus-Robert Müller, Sebastian Pokutta, Markus Reiß

• • EF1-10: Kernel Ensemble Kalman Filter and Inference
    Péter Koltai, Nicolas Perkowski
    
  • EF1-12: Learning Extremal Structures in Combinatorics
    Sebastian Pokutta, Tibor Szabó
  • EF1-14: Sparsity and Sample-Size Efficiency in Structured Learning
    Sebastian Pokutta
  • EF1-15: Robust Multilevel Training of Artificial Neural Networks
    Michael Hintermüller, Carsten Gräser
  • EF1-16: Quiver Representations in Big Data and Machine Learning
    Alexander Schmitt
    
  • EF1-17: Data-Driven Robust Model Predictive Control under Distribution Shift
    Jia-Jie Zhu, Michael Hintermüller
    
  • EF1-18: Manifold-Valued Graph Neural Networks
    Christoph von Tycowicz, Gabriele Steidl
  • EF1-19: Machine Learning Enhanced Filtering Methods for Inverse Problems
    Claudia Schillings
  • EF1-20: Uncertainty Quantification and Design of Experiment for Data-Driven Control
    Claudia Schillings
  • EF1-21: Scaling up Flag Algebras in Combinatorics
    Sebastian Pokutta, Christoph Spiegel
  • EF1-22: Bayesian Optimization and Inference for Deep Networks
    Claudia Schillings, Vladimir Spokoiny
  • EF1-23: On a Frank-Wolfe Approach for Abs-Smooth Optimization
    Sebastian Pokutta, Andrea Walther, Zev Woodstock
  • EF1-24: Expanding Merlin-Arthur Classifiers Interpretable Neural Networks through Interactive Proof Systems
    Sebastian Pokutta, Stephan Wäldchen
  • EF1-25: Wasserstein Gradient Flows for Generalised Transport in Bayesian Inversion
    Martin Eigel, Claudia Schillings, Gabriele Steidl

Successfully completed projects of Emerging Field 1 can be found here.

Digital Shapes (EF2) (2019-2022)

This EF was closed in 2022. The two ongoing research projects were transferred to AA3 and EF3:

• • AA3-14: The Structure within Disordered Cellular Materials (was EF2-2)
    Myfanwy Evans, Francisco Garcia-Moreno, Frank Lutz, John Sullivan
  • EF3-13: A Soft-Correspondence Approach to Shape Analysis (was EF2-5)
    Christoph von Tycowicz, Alexander Bobenko, Daniel Baum, Friederike Fless

Successfully completed projects of Emerging Field 2 can be found here.

Model-Based Imaging (EF3)
Scientists in Charge: Michael Hintermüller, Vladimir Spokoiny, Gabriele Steidl

• • EF3-7: Convolutional Proximal Neural Networks for Solving Inverse Problems
    Gabriele Steidl, Andrea Walther
  • EF3-10: True Excursion Discovery Inference for Imaging Data
    Fabian Telschow
    
  • EF3-11: Quantitative Tissue Pressure Imaging via PDE-Informed Assimilation of MR Data
    Alfonso Caiazzo, Karsten Tabelow, Ingolf Sack
    
  • EF3-12: Integrated Learning and Variational Methods for Quantitative Dynamic Imaging
    Michael Hintermüller, Christoph Kolbitsch, Tobias Schäffter
  • EF3-13: A Soft-Correspondence Approach to Shape Analysis
    Christoph von Tycowicz, Alexander Bobenko, Daniel Baum, Friederike Fless

Successfully completed projects of Emerging Field 3 can be found here.

Multi-Agent Social Systems (EF45)
This Emerging Field evolved from a merger of the former Emerging Fields Particles and Agents (EF4) and Concepts of Change in Historical Processes (EF5).

Successfully completed projects of Emerging Field 4 can be found here.
Successfully completed projects of Emerging Field 5 can be found here.

Scientists in Charge: Christian Bayer, Natasa Djurdjevac Conrad, Wolfgang König, Nicolas Perkowski

• • EF45-1: Agent-Based Modeling of Co-Evolving Opinion and Social Dynamics in Online Media
    Nataša Djurdjevac Conrad, Ana Djurdjevac, Christof Schütte, Carsten Hartmann, Philipp Lorenz-Spreen
  • EF4-5: An Agent-Based Understanding of Green Growth
    Sarah Wolf
  • EF4-7: The Impact of Dormancy on the Evolutionary, Ecological and Pathogenic Properties of Microbial Populations
    Jochen Blath, Maite Wilke Berenguer
  • EF4-8: Concentration Effects and Collective Variables in Agent-Based Systems
    Jobst Heitzig, Péter Koltai, Nora Molkenthin, Stefanie Winkelmann
  • EF4-10: Coherent Movements in Co-evolving Agent–Message Systems
    Felix Höfling, Robert I.A. Patterson
  • EF4-12: Agent-Based Models of SARS-CoV2 Transmission: Multilevel Identification and Network-Based Reduction
    Nataša Djurdjevac Conrad, Martin Weiser, Sarah Wolf, Edda Klipp
    
  • EF4-13: Modeling Infection Spreading and Counter-Measures in a Pandemic Situation Using Coupled Models
    Tim Conrad, Kai Nagel, Christof Schütte
  • EF5-6: Evolution Models for Historical Networks
    Benjamin Ducke, Max Klimm, Guillaume Sagnol