Jennifer Dunne named Fellow of Network Science Society
This week, Jennifer Dunne was named a Fellow of the Network Science Society.
The latest news and events at the Santa Fe Institute
This week, Jennifer Dunne was named a Fellow of the Network Science Society.
This week, Sonia Kéfi received the Erdős–Rényi Prize for young scientists from the Network Science Society.
Ecology is traditionally a data-poor discipline, but tiny microbial worlds offer the quantity of data needed to solve universal questions about abundance and diversity. New research by Jacopo Grilli reveals the fundamental relationship between the environment and the species present in a microbial community and can be used as a starting point for investigating bigger systems.
Using data from humans and other mammals, a team of scientists including researchers from the Santa Fe Institute has developed one of the first quantitative models that explains why sleep times across species and during development decrease as brains get bigger. Crucially, the model identifies a sharp transition at around 2.4 years of age, where sleep patterns change in humans as the primary purpose of sleep shifts from reorganization to repair.
SFI External Professor Raissa D’Souza has joined the Board of Reviewing Editors at Science magazine, one of the world’s top peer-reviewed journals.
Recently, a number of SFI scientists have brought new research frames to bear on the origin of life puzzle. Their work, and that of other leading researchers in the field, is highlighted in a recent Aeon essay.
SFI's Artemy Kolchinsky and David Wolpert present their work exploring the thermodynamics of computation within the context of Turing machines.
In an essay for Aeon magazine, SFI Professor Jessica Flack and SFI Davis Professor Melanie Mitchell describe how the COVID-19 pandemic prompts us to revisit the ways that complex systems retain stability in the biological world. By learning from biological systems, we can begin to shore up the vulnerability inherent in the complex systems that undergird human life.
Leaders of sustainability organizations report on valuable lessons they’ve distilled from their own experiences about successful leadership.
SFI's Jessica Flack, Scott Page, and their fellow founding editors launch new transdisciplinary journal: Collective Intelligence.
If voters gravitate toward the center of the political spectrum, why are the parties drifting farther apart? A new model by SFI's Vicky Chuqiao Yang and her collaborators reveals a mechanism for increased polarization in U.S. politics, guided by the idea of "satisficing"-- that people will settle for a candidate who is "good enough."
A new collection of essays, co-curated by SFI External Professor Andy Dobson, consider unanswered questions about scaling, population biology, ecosystems and communities, collective behavior, and conservation, among other themes.
A new paper by Professor Sid Redner and his collaborators gives a statistical model for optimizing mechanical processes where components wear down and must be reset. It has been chosen as an Editor's Suggestion at the high-profile physics journal, Physical Review Letters.
How biological survival relates to economic choice is the crux of a new paper by SFI's Michael Price and Stanford's James Holland Jones.
Workshops and working groups are among the defining features of science at SFI, but the dividends sometimes follow months or years down the line.
Lauren Ancel Meyers and Sam Scarpino’s analyses inform critical, front-line decisions on pandemic response. Much of their work relies on quantitative methods of network epidemiology, which originated at SFI.
New research shows that spider monkeys use collective computation to figure out the best way to find food.
SFI External Professor Ross Hammond and collaborators have developed a new agent-based computer model that helps policy-makers simulate multiple variations for re-opening. It can incorporate critical factors in determining how to contain COVID-19, such as variations in age, contact networks, activity patterns, and likelihood of infection.
We must use a modeling approach to COVID-19 data that will yield the least biased inference and prediction.
When thinking about reopening schools, an important factor to consider is the rate of community transmission.