Nigel Goldenfeld

Building molecules, studying symbioses between species, and exploring how life evolved

During the earliest months of 2020, COVID-19 seemed like an innocuous event that was too geographically distant to affect the Illinois community. In fact, by March 10th there were only 19 confirmed cases. Nevertheless, Nigel Goldenfeld (BCXT leader/GNDP), former Swanlund Endowed Chair and professor of physics, and Sergei Maslov (BCXT/CABBI), a professor of bioengineering and Bliss Faculty Scholar, were worried. The news from China and Italy was concerning and in four days a significant portion of students, faculty, and staff were going to leave for spring break.

The COVID-19 pandemic has gone on much longer than many predicted in its earliest months. The world has closely watched its progression, with infection rates measured out on graphs in large waves that sometimes taper to extended plateaus, rather than disappearing as traditional epidemiological models would have suggested they should. Meanwhile, scientists have been working to better understand the factors governing the wave and plateau dynamics of the spread of COVID-19, to be able to better forecast future outbreaks in this pandemic and future epidemics.

Swanlund Endowed Chair and Center for Advanced Study Professor in Physics Nigel Goldenfeld (BCXT leader/GNDP) will be closing the chapter on his Illinois career and moving on to the University of California, San Diego (UCSD) this month. There, Goldenfeld will hold the Chancellor’s Distinguished Professorship of Physics where he will continue his work on biological complexity, evolution, ecology and condensed matter theory.

Scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and the University of Illinois Urbana-Champaign (UIUC) have developed a new mathematical model for predicting how epidemics such as COVID-19 spread. This model not only accounts for individuals’ varying biological susceptibility to infection but also their levels of social activity, which naturally change over time. Using their model, the team showed that a temporary state of collective immunity—which they termed “transient collective immunity”—emerged during the early, fast-paced stages of the epidemic.

It sometimes seems a million doesn’t command quite the same attention that it used to. It isn’t mathematically special. And in today’s society, it isn’t even unusually large. We now live in a world where the population is measured in billions, economies are scaled in trillions and computer calculations are counted by the quadrillion.

But it takes on a very special significance when you’re talking about looking after the well-being of your community in the middle of a globally devastating pandemic.

Bees and humans are about as different organisms as one can imagine. Yet despite their many differences, surprising similarities in the ways that they interact socially have begun to be recognized in the last few years. Now, a team of researchers at the University of Illinois Urbana-Champaign, building on their earlier studies, have experimentally measured the social networks of honey bees and how they develop over time.

In biology, phylogenetic trees represent the evolutionary history and diversification of species – the “family tree” of Life. Phylogenetic trees not only describe the evolution of a group of organisms but can also be constructed from the organisms within a particular environment or ecosystem, such as the human microbiome. In this way, they can describe how this ecosystem evolved and what its functional capabilities might be.

The rich complexity of turbulence—with its wide range of length and time scales—poses a major challenge to the development of predictive models based on fluid dynamics. Now, four leading physicists will co-lead an international effort to develop a statistical theory of turbulence. If successful, a statistical theory of turbulence would have broad applications, including in aeronautics, geophysics and astrophysics, medicine, and in the efficient transport of fluids through pipelines.