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

• • EF1-6: Graph Embedding for Analyzing the Microbiome
    Tim Conrad, Stefan Klus, Gregoire Montavon
  • EF1-7: Quantum Machine Learning
    Jens Eisert, Klaus-Robert Müller
  • EF1-8: Incorporating Locality into Fast(er) Learning
    Nicole Mücke
  • EF1-9: Adaptive Algorithms through Machine Learning: Exploiting Interactions in Integer Programming
    Ambros Gleixner, Sebastian Pokutta
  • EF1-10: Kernel Ensemble Kalman Filter and Inference
    Péter Koltai, Nicolas Perkowski
    
  • EF1-11: Quantum and Classical PAC Learning
    Klaus-Robert Müller, Jens Eisert
  • EF1-12: Learning Extremal Structures in Combinatorics
    Sebastian Pokutta, Tibor Szabó
  • EF1-13: Stochastic and Rough Aspects in Deep Neural Networks
    Christian Bayer, Peter-Karl Friz
    
  • EF1-14: Sparsity and Sample-Size Efficiency in Structured Learning
    Sebastian Pokutta
  • EF1-15: Robust Multilevel Training of Artificial Neural Networks
    Michael Hintermüller, Kostas Papafitsoros, 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

Digital Shapes (EF2)
Scientists in Charge: Alexander Bobenko, Hans-Christian Hege

• • EF2-2: The Structure within Disordered Cellular Materials
    Myfanwy Evans, Francisco Garcia-Moreno, Frank Lutz, John Sullivan
  • EF2-3: Spline Models for Shape Trajectory Analysis
    Hans-Christian Hege, Christoph von Tycowicz, Anja Hennemuth, Friederike Fless
  • EF2-5: A Soft-Correspondence Approach to Shape Analysis
    Christoph von Tycowicz, Alexander Bobenko, Daniel Baum, Friederike Fless

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

• • EF3-3: Optimal Transport for Imaging
    Michael Hintermüller, Vladimir Spokoiny, Pavel Dvurechenskii
  • EF3-4: Physics-Regularized Learning
    Carsten Gräser, Ralf Kornhuber, Christof Schütte
  • EF3-6: Deformation Based Regularization of Inverse Problems on Manifolds
    Gabriele Steidl
  • EF3-7: Convolutional Proximal Neural Networks for Solving Inverse Problems
    Gabriele Steidl, Andrea Walther
  • EF3-8: Analysis of Brain Signals by Bayesian Optimal Transport
    Pavel Dvurechenskii, Klaus-Robert Müller, Shinichi Nakajima, Vladimir Spokoiny
  • 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

Particles and Agents (EF4)
Scientists in Charge: Christian Bayer, Wolfgang König, Nicolas Perkowski

• • EF4-1: Influence of Mobility on Connectivity
    Benedikt Jahnel, Wolfgang König
  • EF4-2: Understanding Tipping and Other Dynamical Transitions in Systems Containing Human Agents
    Jobst Heitzig, Péter Koltai, Jürgen Kurths, Christof Schütte
  • EF4-5: An Agent-Based Understanding of Green Growth
    Sarah Wolf
  • EF4-6: Optimal Control of Stochastic Modifed Equations for the Efficient Parametrisation of Deep Neural Networks
    Tobias Breiten, Carsten Hartmann
  • 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

Concepts of Change in Historical Processes (EF5)
Scientists in Charge: Nataša Djurdjevac Conrad, Friederike Fless, Rupert Klein

• • EF5-1: Spreading of Copper Technology in Ancient Times
    Nataša Djurdjevac Conrad, Christof Schütte, Wolfram Schier
  • EF5-3: A Mathematical Theory of Responsibility in Complex Multi-Agent Decision Problems with Uncertainties
    Rupert Klein, Jobst Heitzig, Markus Brill
  • EF5-4: The Evolution of Ancient Egyptian – Quantitative and Non-Quantitative Mathematical Linguistics
    Tonio Sebastian Richter, Ralph Birk, Konstantin Fackeldey, Marcus Weber
  • EF5-5: Spatio-Temporal Modeling of Bioregions
    Heike Siebert, Nataša Djurdjevac Conrad, Sara Varela
  • EF5-6: Evolution Models for Historical Networks
    Benjamin Ducke, Max Klimm, Guillaume Sagnol