Complexity Science Hub. The Complexity Science Hub (CSH) is an independent research institute based in Vienna. It focuses on the study of complex systems, aiming to contribute scientific insights to address the major challenges of our time.

Research 
The Complexity Science Hub (CSH) focuses on the study of complex systems—systems composed of many dynamically interconnected components where the behavior of the whole cannot be easily inferred from the behavior of individual elements. Examples include social networks, supply chains, financial markets, and ecosystems. The aim is to understand the dynamics of such systems to gain insights into the mechanisms behind global challenges, including economic shifts, supply shortages, the climate crisis, pandemics, artificial intelligence, cybercrime, and social crises. A key focus is the assessment of systemic risks in an increasingly globalized world, where vast networks interconnect societies.

A profound scientific understanding of complex systems requires massive datasets. To extract meaningful information from these datasets for decision-making support, CSH researchers develop new paradigms, approaches, methods, and tools using advanced techniques, such as machine learning and artificial intelligence.

The CSH combines methods from mathematics, computer modeling, data science, and network analysis with research questions from various fields, including medicine, economics, ecology, and social sciences. Its research provides the foundation for evidence-based decision-making. By examining interactions within and between complex systems and how they respond to change, the CSH aims to develop realistic interventions to positively influence these systems for the benefit of society.

Research areas are: 

 Foundations of Complex Systems:  New mathematical and statistical methods to better understand complex systems and ultimately manage complexity (complex systems; dynamics; entropy; complexity science; co-evolving networks; equilibrium; emergence; power laws; ...)
 Healthcare & Medicine: Data-driven insights into public health and the optimization of social systems (healthcare system; multimorbidity; public health; network medicine; chronic diseases; pandemics; personalized medicine, gender medicine; ...)
 Health Across Species: Epidemiological patterns of zoonotic diseases and developing prevention strategies (epidemiology; One Health; disease prevention; zoonoses; infectious diseases; pandemic; public health; supply chain; food security; sustainable farming; ...)
 Digital Currency Ecosystems: Functionality and security of emerging financial technologies, including digital currencies and cryptocurrencies (financial innovation; crypto assets; decentralized finance (DeFi), blockchain, token economy, smart contracts; central bank digital currencies (CBDCs); ...)
 Transforming Economies: Rapid changes in modern economies and their consequences (economy; labor market; future of work; economic restructuring; career; teamwork; social networks; investment; innovation strategies; labor force; ...)
 Supply Chain Science: Dynamics of global supply networks to improve resilience (resilience; systemic risk; production networks; supply chain disruptions; network dynamics; big data; economics; financial stability; supply chain transparency; machine learning, sustainability; ...)
 Social Complexity & Collapse: Using historical data to understand and address current crises (Cliodynamics; quantitative history; societal development; inequality; social complexity; ...)
 Algorithmic Fairness: Fairness and equality in the context of digitalization and artificial intelligence (network inequality; algorithmic biases; AI ethics; fairness; gender disparities; homophily; sociophysics, digital humanism; social network modelling; ...)
 Collective Minds: Human adaptation to change, belief formation, and societal polarization (belief dynamics; social networks; group dynamics; computational models; ...)
 Urban Sustainability: Urban growth, redesigning city transport, and optimizing resource use (sustainable cities; Green Transition; urban dynamics; mobility; transportation; city morphology; urbanization; energy and resources; urban footprint; ...)
 Human Migration:  Dynamics and impacts of human migration flows (migration; human mobility; complex dynamics; demography; societal transformation; ...)
 Crime in the Digital Age: New forms and dimensions of global crime, from cybercrime to organized crime (cybercrime; organized crime; criminal networks; cross-border crime; criminal activity modeling; recruitment; data protection; crypto-assets; ransomware; dark web; financial crime; crime prevention strategies; law enforcement support; ...)
 AI & Machine Learning: Innovative machine learning methods to unlock the positive potential of AI (artificial intelligence; machine learning; deep learning; neural networks; scalability; natural language processing; large language models; ...)

Three Core Objectives:

 Go Future. Science for a Better World. The Complexity Science Hub uses science for the benefit of society. Researchers identify and study problems that directly or indirectly affect people every day (and will continue to do so in the future), uncover their causes, and explore possible solutions. By gaining a deep understanding of the complex networks underlying society, they not only address today's challenges but also anticipate future issues, their driving forces, and potential intervention points.
 Creating Skills. Capacities for Future Challenges. The CSH combines qualitative expertise from various disciplines with a profound understanding of quantitative methods and modeling techniques, emphasizing hands-on experience. At the core of this philosophy is the promotion of a research culture that transcends traditional disciplines and structures. Early-career researchers are encouraged to embrace this vision, becoming a new generation of complexity scientists capable of transforming the world through data and science across multiple sectors.
 No Walls. Knowledge for All. The CSH considers it a core mission to make research accessible to a broad audience in an understandable way. To bridge the gap between scientific publications and widely comprehensible information, the CSH uses diverse channels, including press releases, visualizations, social media, and educational materials tailored for various audiences, including children. The CSH is also committed to open science, making data, methods, findings, and models publicly available so others can use them, learn from them, and support data-based decision-making.

Education 
Since its inception, CSH has hosted PhD/Doctoral students who conduct their thesis research at CSH, likewise postdoctoral fellows who conduct research in collaboration with members of the CSH faculty.

In 2024, CSH – with the support of Austrian federal ministries – established the Digital Innovation School, an umbrella structure for research training at the doctoral and postdoctoral levels. The DIS Graduate Program in Complexity Science operates with nine university partners and one federal research institution. Unique features of the DIS PhD program include an annual series of master classes and two research experiences outside of academia. The DIS PostDoc Program focuses on enhancing researchers’ skills in complex systems research, with a specific emphasis on supporting advancement of research through e.g. FAIR data principles.

In CSH offers the following programs for early-stage researchers:

 PostDoc Program
 Graduate Program in Complexity Science (PhD program)
 Complexity Science Winter School
 Visiting Students Program
 Summer Internship Program

CSH Goes School is aimed at teachers, parents, and school-age children. It offers themed worksheets that use interactive data visualizations and dashboards to introduce students playfully to the world of science, demonstrate its application to everyday topics, and spark their curiosity. Additionally, CSH Goes School organizes interactive workshops for school groups from the region and participates in the Long Night of Research and other local science communication events.

Organization and History 
The Complexity Science Hub was founded in 2015 by TU Wien, Graz University of Technology, the Medical University of Vienna, and the AIT Austrian Institute of Technology. Official operations began in 2016. That same year, Vienna University of Economics and Business joined the CSH. In 2018, the University for Continuing Education Krems followed, in 2019 the University of Veterinary Medicine Vienna and the Austrian Federal Economic Chamber, in 2020 Central European University, in 2023 the University of Natural Resources and Life Sciences, Vienna (BOKU), and in 2024 the IT:U Interdisciplinary Transformation University Austria joined. The CSH currently has eleven member institutions across the fields of economics, medicine, technology, life sciences, digitalization, and more.

The CSH is also embedded in an international network of complexity research centers, including the Santa Fe Institute in New Mexico, Arizona State University, the Centro Brasileiro de Pesquisas Físicas (CBPF) in Rio de Janeiro, Sapienza University of Rome, and the Institute for Advanced Study (IAS) in Amsterdam.

Complexity scientist Stefan Thurner has been the first president and scientific director of the CSH since its foundation. The international science advisory board is chaired by the Austrian sociologist Helga Nowotny.

From 2016 to 2024, the CSH was based in Palais Strozzi. In the winter of 2024, the institute relocated to Palais Springer-Rothschild in Vienna’s Landstraße district.

References

External links 

CSH Visualizations
CSH Education

Complexity Science Hub
Complexity Science Hub
Research institutes established in 2016
2016 establishments in Austria
Research institutes