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Scientists usually use a hypergraph model to predict dynamic behaviors. But the opposite problem is interesting, too. What if researchers can observe the dynamics but don’t have access to a reliable model? Yuanzhao Zhang, an SFI Complexity Postdoctoral Fellow, has an answer. In a paper published in Nature Communications, Zhang and his collaborators describe a novel algorithm that can infer the structure of a hypergraph using only the observed dynamics.

SFI Applied Complexity Postdoctoral Fellow Sam Zhang joins the inaugural class of U.S. Research Software Sustainability Institute (URSSI) Early-Career Research Fellows. The fellowship supports “research projects focused on improving current disciplinary or domain practices in developing science software,” especially explorations of “emerging best practices (or problems) in sustaining” that software.

SFI External Professor Raissa D’Souza (UC Davis) has been elected as a 2024 Fellow at the American Association for the Advancement of Science (AAAS).

In many careers, a person must learn foundational skills before advancing more deeply into their profession. A recent paper in Nature Human Behavior mapped the dependency relationships between workplace skills, identifying a nested structure in many professions, where advanced skills depend on prior mastery of broader skills. This nestedness, they found, has significant implications for wage inequality and career mobility in increasingly complex labor markets.

Aiming to chart a more sustainable path for governing our nation’s grid, representatives spanning physics, law, energy regulation, economics, and even evolutionary dynamics is meeting April 9–11 at SFI for a working group on “Governance Institutions for a Polycentric and Technologically Complex Electric Power Grid.” 

To avoid the unintended consequences of climate policy, we need to better understand how climate policies and people’s values coevolve. A recent working group led by Katrin Schmelz and Sam Bowles met to investigate. 

Over the past three years, C. Brandon Ogbunu has become a familiar face at SFI as an External Professor. In February, he joined SFI as a part-time Resident Professor.

When comparing two objects, people either rely on internal memories of these objects or run their hands and eyes over them to directly perceive their similarity. The latter approach, a shortcut that offloads cognition to the active perceptual operations like eye or hand movements, requires a lower memory burden. In a study published in the journal Attention, Perception, & Psychophysics, SFI Complexity Postdoctoral Fellow Marina Dubova and SFI Research Fellow Arseny Moskvichev demonstrate that it is also more effective.

SFI External Professor and Science Steering Committee member Michelle Girvan (University of Maryland) has been elected President of the Network Science Society, an organization that supports an interdisciplinary research community dedicated to investigating the phenomena, modeling, and behavior of networks.

In The Power of the Invisible: The Quantessence of Reality, former SFI External Professor Sander Bais offers a three-volume set that reviews classical physics, dives deeper into quantum mechanics, and explores the underpinnings of complex systems, all in a coffee-table-worthy package. "This remarkable tour de force covers all of physics and much of science in general with elan, insight, and humor, imparting a feeling of awe for the profundity of the laws of the universe," writes SFI External Professor Doyne Farmer. "It encapsulates the wisdom that can only be achieved by a brilliant physicist at the end of a long career, and is a tribute to the mystique and magic of science." 

SFI External Professor Mason A. Porter (UCLA) has received the 2025 George Pólya Prize for Mathematical Exposition from the Society for Industrial and Applied Mathematics (SIAM) for “his outstanding exposition of the mathematical sciences to audiences at all levels and interests.”

A new paper in PNAS shows that the idea of “taking turns” could help resolve the 1960s paradox of the plankton — and better predict how climate change will remake our oceans.

Since the last major ice age, populations of large animals have dwindled. These declines have directly affected climate change, wildfires, and natural resources. A March 17-19 working group brings together historical ecologists, conservation biologists, computational modelers, and archaeogeneticists to explore these impacts further and develop new tools for predicting ecosystem resilience and preventing future megafauna loss.

Using a variety of analogy puzzles, SFI researchers have shown that the reasoning abilities of OpenAI’s GPT-4 model fall short when faced with small changes. Recognizing the limitations of these tools is critical to knowing when and to what extent they can be trusted.

In a recent study in Physical Review Letters, SFI Complexity Postdoctoral Fellow Aanjaneya Kumar and colleagues show that the margin of victory for any election can be predicted solely by the voter turnout.

Medieval friar William of Ockham posited a famous idea: always pick the simplest explanation. Often referred to as the parsimony principle, “Ockham’s razor” has shaped scientific decisions for centuries. But lately, incredibly complex AI models have begun outperforming their simpler counterparts. A new paper in PNAS argues that by relying too much on parsimony in modeling, scientists make mistakes and miss opportunities.

Applications for the third Complexity Global School (CGS) are now open. The school will be hosted at Universidad de los Andes in Bogotá, Colombia, and applicants from all countries are eligible to apply. Supported by the Omidyar Network and the Ford Foundation, the school is free, with expenses covered, for all admitted students. Applications are due by March 16, 2025.

Cultural traits — the information, beliefs, behaviors, customs, and practices that shape the character of a population — are influenced by conformity, the tendency to align with others, or anti-conformity, the choice to deliberately diverge. A new way to model this dynamic interplay could ultimately help explain societal phenomena like political polarization, cultural trends, and the spread of misinformation. 

Over the past three years, SFI has hosted an annual Complexity-GAINs school — two-week-long programs organized around a theme for Ph.D. students — in different locations in Europe. The third and final school, focused on ecological resilience and persistence, was held last October in Sète, France.

Half a century ago, economic research took a little-noticed yet dramatic departure from the study of concepts most people might be familiar with from Econ 101. The field shifted from an almost exclusive focus on market transactions and government policies to include societal interactions for which supply-and-demand models don’t work. A new paper in Economics Letters uses a machine-learning technique to document this shift away from state-related topics toward a focus the authors term "civil society."