The 2026 Conference on Complex Systems will be held in Binghamton, New York, USA. Binghamton has a long history of creativity and innovation. The Greater Binghamton area has historically been called “the Valley of Opportunity” and attracted many immigrants (especially from Europe) since the mid-1800s, which has made the region’s rich and diverse culture and demographics. It is the birthplace of IBM (International Business Machines), Link Flight Simulator, McIntosh Laboratory, and a number of other pioneering ventures, fostering a spirit of ingenuity that continues to thrive.

Located at the confluence of the Susquehanna river (one of the oldest rivers in the world) and the Chenango river, the region boasts stunning natural beauty and offers ample opportunities for outdoor recreation, from hiking and biking to fishing and kayaking. In particular, in mid-October when CCS 2026 is held, the Binghamton area will showcase its renowned and breathtaking fall foliage. Furthermore, a vibrant arts and culture scene flourishes here, with numerous galleries, theaters, and music venues providing enriching experiences.

CCS 2026 will be held primarily in person on the main campus at Binghamton University, with an online participation option via Zoom.

Read the full article at: ccs2026.github.io

The Spanish Society of Complex Systems (CS³ Spain) was founded in 2022, during the International Conference on Complex Systems held in Palma de Mallorca, with the aim of strengthening the community of complex systems researchers in our country.

Since then, the Spanish Chapter has held three meetings: in Santander (2023), in Barcelona (2024) and in Madrid (2025), consolidating itself as a reference space for the exchange of ideas and interdisciplinary collaboration.

The 4th Meeting of the Spanish Society of Complex Systems will take place in Seville, from January 21 to 23, 2026, at the emblematic Uruguay Pavilion, headquarters of the University of Seville.

More at: cs3.es

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