The MATH+ Emerging Fields (EF) represent interdisciplinary research areas where MATH+ pioneers innovative work across science, technology, and the humanities. The three EFs, Learning-Informed Optimization, Decision Support, and Multi-Agent Systems, aim to push the boundaries of mathematical innovation and drive high-impact applications. Led by expert PIs, each EF aligns with the overarching goal of tackling complex real-world challenges through advanced mathematical approaches. Initially focused on the three topics mentioned above, the EFs will adapt and expand as new research agendas and perspectives emerge, contributing to groundbreaking interdisciplinary work.
Learning- Informed Optimization (formerly EF1: Extracting Dynamical Laws from Complex Data)
Scientists in Charge: Jens Eisert, Gabriele Steidl, Max Zimmer
-
- EF1-23: On a Frank-Wolfe Approach for Abs-Smooth Optimization
Sebastian Pokutta, Andrea Walther, Zev Woodstock - EF-LI-Opt-1: Neural Generative Models for Algebraic Curves
Michael Joswig, Sebastian Pokutta - EF-LI-Opt-2: Exploding Velocity Fields in Generative Neural Flows: Analysis and Circumvention
Gabriele Steidl, Peter K. Friz - EF-LI-Opt-3: Agentic AI in Mathematics
Sebastian Pokutta
- EF1-23: On a Frank-Wolfe Approach for Abs-Smooth Optimization
Completed projects of Emerging Field 1 can be found here.
Multi-Agent System (formerly EF45: Multi-Agent Social Systems)
This Emerging Field evolved from a merger of the former Emerging Fields Particles and Agents (EF4) and Concepts of Change in Historical Processes (EF5).
Completed projects of Emerging Field 4 can be found here.
Completed projects of Emerging Field 5 can be found here.
Scientists in Charge: Natasa Djurdjevac Conrad, Nicolas Perkowski, Sarah Wolf
-
- EF45-2: Effective Stochastic Simulation of Adaptive AB models
Max von Kleist - EF-MA-Sys-1: Emergent Structures in Multi-Component Systems for Embryogenesis
Katharina Hopf, Matthias Liero, Markus Mittnenzweig - EF-MA-Sys-2: Information Flow & Emergent Behavior in Complex Networks
Benedikt Jahnel, Lukas Lüchtrath
- EF45-2: Effective Stochastic Simulation of Adaptive AB models
Completed projects of Emerging Field 45 can be found here.
Decision Support (formerly EF6: Decision Support in the Public Sector)
Scientists in Charge: Tobias Breiten, Stefan Flasche, Max von Kleist
-
- EF-Dec-Supp-1: Bayesian Perspective on Optimal Control under Uncertainty
Tobias Breiten, Anna Maria Hartkopf, Max von Kleist, Claudia Schillings - EF-Dec-Supp-2: Coevolution of Opinion and Epidemic dynamics for Decision Support
Nataša Djurdjevac Conrad, Max von Kleist, Claudia Schillings, Christof Schütte - EF-Dec-Supp-3: Moving Sensor and Actuator Design for Dynamical Systems
Tobias Breiten, Daniel Walter
- EF-Dec-Supp-1: Bayesian Perspective on Optimal Control under Uncertainty
Completed projects of Emerging Field 45 can be found here.
During the first funding period, MATH+ also explored the following Emerging Fields:
Digital Shapes (EF2) (2019-2022)
Completed projects of Emerging Field 2 can be found here.
Model-Based Imaging (EF3) (2019-2024)
Some projects have been moved to Application Area 5: Variational Problems in Data-Driven Applications.
Completed projects of Emerging Field 3 can be found here.