“How do groups of animals behave? How do billions of particles interact? How do populations migrate or reach consensus? How does a pandemic spread?” These are seemingly disparate questions. But, as Maurizio Porfiri, a complex-systems expert and Institute Professor at the NYU Tandon School of Engineering, with affiliations across multiple departments as well as the Center for Urban Science and Progress, points out, they all involve deciphering the interactions within collective dynamics. And answering those questions by identifying patterns in data that others may not appreciate can offer insights into how to address a diverse spectrum of issues that affect people’s everyday lives — including how skyscrapers are built, how healthcare is delivered, and how lawmakers should think about firearm policies.
Porfiri gathers raw time-series data — in essence, observations obtained through repeated measurements that reveal how a variable evolves over time — and analyzes it to come up with inferences. Since data scientists don’t always have the luxury of perfect datasets — some may include too many data points and others too few — it’s often necessary to build mathematical models to cull or extrapolate information. “What I’m really doing is building basic algorithmic tools that can be applied in a variety of areas,” he says.
“For example, at one time in my career I began working on the interactions between live and robotic fish to understand collective animal behavior; then, I saw how some of these methodological concepts could be adapted to the study of human behavior, such as what spurs gun purchases and how people behave in a pandemic, or even how ions interact in active materials.”
Porfiri, a native of Italy, has long sought to tackle problems from a broad perspective. “As an undergraduate, I tried courses in environmental engineering and aerospace engineering, but I felt boxed in,” he recalls. “I didn’t want to study the details of how to build a plane; I wanted to gain a fundamental understanding of what allowed a plane to fly in the first place. In the end, the only reason I graduated as an electrical engineer was that I was allowed only two changes in my curriculum, otherwise I would have tried them all and never graduated.” Still, he says, it is this diverse background that allows him to see similarities, analogies, and patterns that might have escaped someone with a more homogenous background.
One of the multifaceted projects Porfiri has undertaken is untangling the sometimes surprising causal relationships among factors contributing to firearm-related harm. In an area where there’s no shortage of bumper sticker slogans (“If guns are outlawed, only outlaws will have guns.” “Protect kids, not guns.”), it’s not as clear cut as some may believe. With support from the National Science Foundation and the National Collaborative on Gun Violence Research, Porfiri is exploring the influence of legislation on firearm acquisition, what media coverage adds to the mix, and the incidence of mass shootings. His aim is to provide nonpartisan common-sense guidance that will inform legislative actions to mitigate mass shootings, while minimizing the adoption of ineffective policies that would unnecessarily limit firearm owners’ rights.
He’s addressing other threats to health and wellbeing too: even before COVID-19 hit, Porfiri and his team were working on an app called StopTheSpread and studying how the interconnections between individuals, how they moved through their communities, and how the adoption of measures like vaccinations and hand-washing could impact the spread of infectious diseases like the flu. When the pandemic hit, they pivoted, turning to data from New Rochelle (the New York suburb first seriously afflicted by COVID-19) and building a mathematical model specifically for the city’s unique social and transportation structures. The model can help health and government leaders make smart, up-to-date testing and contact-tracing decisions — and can inform how outbreaks are handled in the future.
In addition to pandemic spread, Porfiri is looking at the intersection of human behavior and data to better equip healthcare professionals for a technology-driven era. If you’ve been to a doctor or hospital any time in recent years, you’ve probably noticed how many digital tools healthcare providers now have at their disposal, from electronic record-keeping systems to remote patient-monitoring and telehealth devices. But while Data-Intensive Technologies (DIT) present huge potential upsides, there is still reluctance on the part of some professionals to embrace them, simply because they don’t understand how to interact with such massive quantities of data and don’t feel empowered to use it effectively. Porfiri and his multidisciplinary team of collaborators are working with 1,000 care sites across the country and involving health professionals in a wide variety of roles to learn how to lower the barriers to adopting DIT while enabling the human-centered healthcare that strengthens clinician-patient relationships.
Humans are not the only members of the Animalia Kingdom to incite Porfiri’s interest. Once named to Popular Science’s “Brilliant 10” list for his work with biologically inspired aquatic robots, he is now studying coordinated swimming among schools of fish. He explains that, at sufficient speeds, schooling fish may prefer to swim in a "phalanx" formation, where there is no leader and every fish beats their tail almost in synchrony. Currently, it’s difficult to discern what’s behind that phenomenon because we lack adequate data-driven techniques to disentangle causes from effects in coordinated swimming. Developing those techniques has implications in areas far beyond the sea, including the discovery of how clusters of tall buildings react to wind gusts and how the mechanics of human vocal production work.
Porfiri’s exploration of the undersea world has extended to the Venus flower basket sponge (E. aspergillum), a deep-sea organism with a paradoxical ability to withstand tremendous ocean forces in spite of its crystalline, filigree-like structure. Porfiri and his collaborators, seeking to understand how the sponge interacts with its environment in order to thrive in the face of powerful ocean currents, turned to the CINECA high-performance computing center in Italy. With the help of the Marconi100, which is capable of building comprehensive simulations using billions of dynamic, temporospatial data points in three dimensions, they were able to create a first-ever simulation of the deep-sea sponge and how it responds to and influences the flow of nearby water. And while the sponge’s remarkable structural properties might seem fathoms removed from human-engineered structures, insights into how the organism’s latticework of holes and ridges influences the hydrodynamics of seawater in its vicinity could lead to advanced designs for buildings, bridges, marine vehicles and aircraft, and anything that must respond safely to forces imposed by the flow of air or water.
It is recognizing patterns in data, and appreciating what patterns in the natural environment can tell us about our constructed ones, that has enabled Porfiri to delve into topics as wide ranging as gun violence, smart materials, and doctor-patient relationships. “You first have to decide upon the questions you want to answer — whatever those questions may be — and then you can look to the data for answers,” he explains.
With so many important topics to explore, how does he decide where to turn his attention? It may be a less “engineered” process than you would imagine. “Topics catch my interest,” he explains. “It might be a discussion I’m having with my wife, a friend, or a colleague about the environmental hazards facing cities or a story in the newspaper about an increase in gun purchases. And then my mind starts working.”
This content is sponsored and provided by NYU Tandon School of Engineering. The editorial team at Inside Higher Ed had no role in its creation.