Thematic Einstein Semester on

The Mathematics of Complex Social Systems: Past, Present, and Future

Summer Semester 2022

Organizers

Nataša Djurdjevac Conrad (ZIB)
Benjamin Ducke (DAI)
Friederike Fless (DAI)
Stefan Klus (U Surrey)

Jürgen Kurths (PIK/HU)
Christof Schütte (ZIB/FU)
Stefanie Winkelmann (ZIB)
Sarah Wolf (FU/GCF)

The semester is organized within the framework of the Berlin Mathematics Research Center Math+ and supported by the Einstein Foundation Berlin.

We are committed to fostering an atmosphere of respect, collegiality, and sensitivity. Please read our MATH+ Collegiality Statement.

Registration

To register for an event / events within the Thematic Einstein Semester please use the link: https://www.conftool.net/tes-summer-2022/

The registration closes 10 days prior to an event.

Scope of the Semester

The Thematic Einstein Semester The Mathematics of Complex Social Systems: Past, Present, and Future aims at unlocking the potential for mathematical modeling and reasoning within the extremely large and diversified fields of study that constitute modern Social Sciences and the Humanities. It shall bring together young researchers and experienced scholars from mathematics and other disciplines to focus on complex social systems, with a two-fold focus on agent-based models (ABMs) and data-driven methods. The TES will consist of specific events, continuous activities over the semester, and research visits.

Opening Day (April 25, 2022)

To kick off the TES, the opening day will introduce a spectrum of approaches to mathematical analysis of past and present social systems. Also, it will present a few characteristic data sets that shall be objects of study in the TES. We invite interested students to participate and investigate these data sets throughout the semester in small interdisciplinary groups. Further information can be found here.

 

The opening day will be held in conjunction with Workshop I.

Workshop I: Data-driven modeling and analysis (April 26, 2022)

The goal of this workshop is to provide an overview of data-driven methods for the analysis of time-series data. Given only measurement or simulation data, these methods can be used to extract global properties of the underlying system such as time scales and metastable sets or to directly learn the governing equations of the system. Further information can be found here.

Workshop II: Data past and present (May 17-18, 2022)

In this workshop research data becomes the proverbial rubber that meets the road. Models, data and interpretations from a range of research domains will be juxtaposed and illustrated by worked case studies. This will include data sampled from a present population in a controlled manner, as well as more extreme data about past populations that is fragmentary and results from only weakly controlled sampling. An overarching aim will be to identify the manifold sources of bias, uncertainty and error in real-world research data, and to scrutinize data-derived conclusions. Another focus will be on formal methods and frameworks for handling incomplete data and representing uncertainty. Further information can be found here.

Workshop III: Stochastic modeling of complex social systems (June 7-8, 2022)

This workshop will provide an overview of stochastic modeling approaches for understanding complex social systems, such as agent-based modeling (ABM), network modeling and hybrid modeling approaches for multi-scale systems. Of particular interest will be new simulation techniques, numerical analysis, computational methods and model reduction approaches. Potential focal areas are model derivation and inference for complex social systems, analysis and control of spreading processes, concepts and measurement of transition dynamics and tipping behaviour, as well as simulation and model reduction of multi-scale social dynamics. This workshop will be held in combination with the summer school. Further information can be found here.

Summer school (June 9-17, 2022)

In cooperation with the BMS and the School of Complex Adaptive Systems at Arizona State University, this summer school shall bring together an international and interdisciplinary group of Master and Ph.D. students to learn about different modeling approaches for complex social systems through a series of expert lectures and hands-on workshops. Topics will include agent-based and network models with applications, for example, in opinion dynamics and the evolution of cooperation, as well as economics and archeological research.

 

Invited teachers: Joffa Applegate (Arizona State University), Sven Banisch (Karlsruhe Institute of Technology), Renaud Lambiotte (University of Oxford), Iza Romanowska (Aarhus University), Pawel Romanczuk (Humboldt Universität zu Berlin), Martin Rosvall (Umea University), Michael Schaub (RWTH Aachen University), Ingo Scholtes (University of Wuppertal), and Shade Shutters (Arizona State University).

 

The application deadline is April 30, 2022. Further information and application details can be found here.

Final conference: Mathematics of complex social systems (September 19-20, 2022)

The final conference will synthesize the TES’ insights and outcomes. Alongside several high-level keynotes, MATH+ work on complex social systems as well as projects carried out throughout the semester will be presented.

The events will be complemented by the following semester-long activities:

Einstein lecture series

Experienced visiting and local researchers shall present recent work on mathematics of complex social systems in a regular series of talks (on campus / online) throughout the summer semester. Further information can be found here.

BMS course & open seminar

A weekly seminar at FU Berlin invites students to delve into a selection of works from the literature related to the mathematics of complex social systems.

Seminar: Mathematical modeling of complex social systems

TES Data Challenge

Groups of students are invited to participate in the TES data challenge and  investigate the TES’ characteristic data sets throughout the semester, following the three disciplines of modeling, simulation, and analysis. Experts from the field will offer their support regarding mathematical methods and data analysis. The three best groups will be awarded and will have the opportunity to present their results at the TES Final Conference. Further information can be found here.