News + Events

SFI's research network includes renowned scholars affiliated with universities and institutions from around the world. This year, SFI welcomes four new external professors.   

Research News Briefs highlight new studies from the SFI community published in the last quarter. The following briefs appeared in SFI's Summer 2020 Parallax newsletter. 

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.

SFI's Applied Complexity Network has ramped up virtual offerings, increasing participation amongst both ACtioN members and external SFI faculty.

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.

Like many events in the COVID era, the bi-annual Postdocs in Complexity conference has moved online. Participants continue to collaborate despite some of the inherent challenges.

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.  

InterPlanetary Transmissions: Stardust, a record of the proceedings of the second annual InterPlanetary Festival, has launched from the SFI Press.

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.

Human cognition and cultural norms have changed the composition of human portraits, according to a new analysis of European paintings from the 15th to the 20th century. The study, led by SFI Omidyar Fellow Helena Miton, examined "bias" in 1831 paintings by 582 unique European painters.

Our thoughts are with the many victims of disease, abuse, injustice, and exclusion. Black lives and Native lives matter. Our community of complexity researchers are aligned with all who are committed to freedom, justice, diversity, opportunity, and empiricism. We stand with those who strive to provide the most powerful ideas, methods, and tools pursuant to a civil and equitable society. We add our voice to the moment, defend freedom of expression, and offer all that we can in pursuit of a safer and fairer world.

Launched in early April, the online “Complexity of COVID-19” course is a resource for families and communities to think through the broad-reaching consequences of this pandemic in real time.

To present expert perspectives on the complexities of the COVID-19 pandemic, SFI has launched an online series called “Transmission.”

When disease modelers map the spread of viruses like the novel coronavirus, Ebola, or the flu, they traditionally treat them as isolated pathogens. Under these so-called “simple” dynamics, it’s generally accepted that the forecasted size of the affected population will be proportional to the rate of transmission. But according to former SFI postdoc Laurent Hébert-Dufresne at the University of Vermont and his co-authors Samuel Scarpino at Northeastern University, a former Omidyar Fellow, and Jean-Gabriel Young at the University of Michigan, the presence of even one more contagion in the population can dramatically shift the dynamics from simple to complex.

In the field of computer science, recent advances in machine learning have begun to produce tools that could be used to mine the vast trove of communiqués in cyberspace that hold patterns that can provide rich insights into how our minds work. An SFI working group, which met online in April, brought together psychologists and computer scientists to explore how the two fields can collaborate. 

An online workshop, held March 31, explored what could happen after the first wave of the COVID-19 pandemic, once social distancing guidelines are relaxed.