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 three 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
    
  • EF1-11: Quantum Advantages in Machine Learning
    Klaus-Robert Müller, Jens Eisert
  • EF1-16: Quiver Representations in Big Data and Machine Learning
    Alexander Schmitt
  • 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
  • EF1-23: 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

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

The projects EF1-14, -15, -18, -22, and -25 have been moved to Application Area 5: Variational Problems in Data-Driven Applications.

Digital Shapes (EF2) (2019-2022)

This EF was closed in 2022.
Successfully completed projects of Emerging Field 2 can be found here.

Model-Based Imaging (EF3) (2019-2024)
This EF was closed in 2024.

Some projects have been moved to Application Area 5: Variational Problems in Data-Driven Applications.

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

• • EF45-1: Informing Opinion Dynamics Models with Online Social Network Data
    Nataša Djurdjevac Conrad, Ana Djurdjevac, Christof Schütte, Carsten Hartmann, Philipp Lorenz-Spreen
  • EF45-2: Effective Stochastic Simulation of Adaptive AB models
    Max von Kleist
  • EF45-3: Data Transmission in Dynamical Random Networks
    Benedikt Jahnel
  • EF45-4: Hybrid Models for Large Scale Infection Spread Simulations
    Tim Conrad, Kai Nagel, Christof Schütte
  • EF45-5: A New Approach to Metastability in Multi-Agent Systems
    Maximilian Engel
  • EF4-5: An Agent-Based Understanding of Green Growth
    Sarah Wolf
  • EF4-10: Coherent Movements in Co-evolving Agent–Message Systems
    Felix Höfling, Robert I.A. Patterson

Successfully completed projects of Emerging Field 45 can be found here.

Decision Support in the Public Sector (EF6)

Scientists in Charge: Max von Kleist, Claudia Schillings

• • EF6-1: Heterogeneous Data Integration to Infer SARS-CoV-2 Variant-Specific Immunity for Risk Assessment and Vaccine Design
    Max von Kleist, Claudia Schillings, René Henrion
  • EF6-2: Deliberation Processes in Citizens’ Assemblies: An Optimal Experimental Design Perspective
    Sven Wang, Jobst Heitzig, Claudia Schillings
  • EF6-3: Labour in an Agent-Based Understanding of Green Growth
    Sarah Wolf