Complexity science studies how a large collection of components can spontaneously self-organize to exhibit non-trivial, unpredictable global structures and behaviors at larger scales, having many applications with daily life impacts, e.g., climate change, financial markets, healthcare, polarization, and technological networks. Characteristics of these systems, such as having non-linear emerging dynamics and being adaptive, pose unique ethical challenges, as traditional normative ethical approaches often struggle to account for such dynamic and intricate interactions.

This one-day interdisciplinary workshop aims at bridging the gap between researchers in complexity science and ethics and offers a new perspective on why ethics discussions are necessary in such a complex research realm.

More at: ethics.dsi.uzh.ch

Since 2001, the Nonlinear Science Working Group has been serving the complexity science community by organizing the Disordered Systems Symposia (DSS), one of the oldest and longest-running international events dedicated to disordered systems, complexity, and nonlinearity. DSS provides a vital platform that brings together leading specialists, early-career researchers, and participants from diverse fields to exchange ideas, foster collaboration, and advance research in complexity science.

With DSS-2025, we continue two initiatives introduced to further serve and expand the community. The Murray Gell-Mann Memorial Lectures honor his pioneering contributions to complexity science and his visionary spirit. The WOMPLEXITY initiative promotes the visibility of women in complexity science. These efforts demonstrate our ongoing commitment to supporting diversity, inclusion, and excellence within the complexity science community.

More at: www.non-linearscience.org

The aim of the school is to present methodological, computational and machine learning methods for complex networks analysis, with applications spanning a wide range of fields.

The school will present a comprehensive view of the theoretical aspects of challenging topics in network theory, including higher order networks, diffusive models on networks, probabilistic and machine learning approaches, as well as computational methods. A wide range of applications will be explored during the lectures, including socio-economic and financial applications.

A Python tutorial held by lecturers/teaching assistants will follow the lecture to show the implementation of the methods studied during the theoretical class and the proposed application.

More at: tcn2025.wordpress.com

IC2SMA2 2026 aims to create a new international venue that can unite scholars, practitioners and students from diverse fields to address various real-world challenges and opportunities using methodologies of complex systems modeling and analysis. The conference will showcase cutting-edge modeling/analysis methods, interdisciplinary applications, and innovative solutions, fostering collaboration and sparking new ideas. Its 2026 edition will have a particular focus on the applications to education and society. By integrating insights from systems science, mathematics, computer science, engineering, economics, social sciences, psychology, healthcare, education, and many others, we seek to advance understanding and application in these crucial areas. Join us to explore how multidisciplinary approaches can drive improvements in our society!
Organized in Hybrid Mode by CHRIST University, Pune Lavasa, India & Binghamton University, State University of New York, USA

More at: ic2sma2.christuniversity.in

Since its inception in 1998, ANTS has been a highly selective, single-track meeting that provided a forum for discussing advances in the field of swarm intelligence. It solicits submissions presenting significant, original research from researchers and practitioners of any area related to swarm intelligence.

Swarm intelligence is an interdisciplinary and rapidly evolving field, rooted in the study of self-organizing processes in both natural and artificial systems. Researchers from disciplines ranging from ethology to statistical physics have developed models that explain collective phenomena, such as decision-making in social insect colonies and collective movements in human crowds. Swarm-inspired algorithms and methods have proven effective in solving complex optimization problems and creating multi-robot and networked systems of unparalleled resilience, adaptability and scalability. Applications of swarm intelligence continue to grow and become increasingly critical for addressing societal challenges such as environmental sustainability, food security, health, and global conflicts.

The 2026 edition’s theme is “reaching beyond – swarm intelligence across systems, disciplines, and communities”. The meeting seeks to encourage new perspectives, help bridge traditional boundaries and enable open debate on what could be ambitious, exploratory, and groundbreaking endeavors to embark on.

More at: ants2026.org