A hyperlink network from English Wikipedia, with only 0.1% of articles (nodes) and their connections (edges) visualized. Seven different reader journeys through this network are highlighted in various colors. The network is organized by topic and displayed using a layout that groups related articles together. (Image: Dale Zhou)
At one point or another, you may have gone online looking for a specific bit of information and found yourself “going down the Wiki rabbit hole” as you discover wholly new, ever-more fascinating related topics — some trivial, some relevant — and you may have gone so far down the hole it’s difficult to piece together what brought you there to begin with.
According to the University of Pennsylvania’s Dani Bassett, who recently worked with a collaborative team of researcher to examine the browsing habits of 482,760 Wikipedia readers from 50 different countries, this style of information acquisition is called the “busybody.” This is someone who goes from one idea or piece of information to another, and the two pieces may not relate to each other much.
“The busybody loves any and all kinds of newness, they’re happy to jump from here to there, with seemingly no rhyme or reason, and this is contrasted by the ‘hunter,’ which is a more goal-oriented, focused person who seeks to solve a problem, find a missing factor, or fill out a model of the world,” says Bassett.
In the research, published in the journal Science Advances, Bassett and colleagues discovered stark differences in browsing habits between countries with more education and gender equality versus less equality, raising key questions about the impact of culture on curiosity and learning.
Dani S. Bassett is the J. Peter Skirkanich Professor at the University of Pennsylvania with a primary appointment in the School of Engineering and Applied Science’s Department of Bioengineering and secondary appointments in the School of Arts & Sciences’ Department of Physics & Astronomy, Penn Engineering’s Department of Electrical and Systems Engineering, and the Perelman School of Medicine’s Departments of Neurology and Psychiatry.
Representing Bach’s pieces as networks reveals hidden structures in his music. (Credit: Suman Kulkarni)
Even today, centuries after he lived, Johann Sebastian Bach remains one of the world’s most popular composers. On Spotify, close to seven million people stream his music per month, and his listener count is higher than that of Mozart and even Beethoven. The Prélude to his Cello Suite No. 1 in G Major has been listened to hundreds of millions of times.
What makes Bach’s music so enduring? Music critics might point to his innovative harmonies, complex use of counterpoint and symmetrical compositions. Represent Bach’s music as a network, however, where each node stands for one musical note, and each edge the transition from one note to another, and a wholly different picture emerges.
In a recent paper in Physical Review Research, Dani S. Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering within the School of Engineering and Applied Science, in Physics & Astronomy within the School of Arts & Sciences, and in Neurology and Psychiatry within the Perelman School of Medicine, and Suman Kulkarni, a doctoral student in Physics & Astronomy, applied network theory to Bach’s entire oeuvre.
The paper sheds new light on the unique qualities of Bach’s music and demonstrates the potential for analyzing music through the lens of networks. Such analysis could yield benefits for music therapists, musicians, composers and music producers, by giving them unprecedented quantitative insight into the structure of different musical compositions.
“This paper provides a starting point for how one can boil down these complexities in music and start with a simple representation to dig into how these pieces are structured,” says Kulkarni, the paper’s lead author. “We applied this framework to a dozen types of Bach’s compositions and were able to observe quantitative differences in how they were structured.”
Younger scientists often ask him about exploring multiple fields, Balasubramanian says. The advice he offers is to “have a central line where you have credibility, where you’ve established that you’re really, really good at what you do, and you can be trusted.” (Image: Eric Sucar)
Academia is a long journey of specialization and behind any professor’s CV are long hours of research and study. While the path can be direct for some, for others there’s a pivot, a moment or experience that changes the course of that journey.
Penn Today spoke with four professors whose academic paths diverged, to learn about the trajectory of their interdisciplinary work. Vijay Balasubramanian traverses the boundaries of physics and neuroscience. Tukufu Zuberi is a demographer-turned-curator. Brittany Watson integrates education, research, and veterinary medicine. Amy Hillier began her career studying historical mortgage redlining and moved into supporting trans youth.
Vijay Balasubramanian The Cathy and Marc Lasry Professor of Physics in the School of Arts & Sciences
Wandering through Kolkata’s markets in India stimulates the mind. Hawkers’ cries pass through the inner ear as electrical signals; the pungent, earthy smell of turmeric enters the brain through olfactory sensory neurons. In 1976, a 7-year-old Vijay Balasubramanian had his own market revelation through a bookseller’s portico, where the cover of a slim volume showed a man peering through a microscope lens and a smattering of white paint scattered like stars across the firmament of man and machine.
“What is a scientist?” the book asked, running through a series of exciting adventure shots: archeologic discovery, venom extraction, missile control. In that moment, Balasubramanian knew he would be a scientist. It looked, he says, “amazingly cool.”
When he arrived at the Massachusetts Institute of Technology, Balasubramanian wanted to study the fundamental laws of nature. “So that’s physics,” he says. While earning his doctoral degree at Princeton University, a mentor suggested Balasubramanian read papers in the burgeoning field of neuroscience. It immediately resonated. “Oh my god, this stuff is so cool,” Balasubramanian thought. “But the final year of a Ph.D. is not the time to switch.”
He earned his degree and took a position as a junior fellow of the Harvard Society of Fellows. During the day, he worked on string theory and the information loss paradox for black holes. But in the evening, he would moonlight in a neuroscience lab.
As a young theoretical physicist at Penn, Balasubramanian met Peter Sterling. A former Freedom Rider and professor of neuroscience at the Perelman School of Medicine, Sterling was “a true intellectual,” Balasubramanian says. He knew everything, was interested in everything, and would talk with anybody.
The pair wrote a series of papers together regarding information processing and transmission. “He’s so quick and so much fun and so lively,” Sterling says of Balasubramanian. “He’s fearless; there’s nothing he won’t try.”
While in Cairo with wife Heather J. Sharkey, professor of modern Middle Eastern and North African history at Penn, Balasubramanian prepared a neuroscience grant and submitted it to the National Science Foundation, “sort of on a whim,” he says. “I put it in from an internet café on an island in the middle of the Nile.” He got the grant and started a research group.
After that, Balasubramanian says, “I was off and running.”
“I was certainly told,” Balasubramanian says of his work in neuroscience, “do not do this before tenure.” But, if he waited, “then I’d be too set my ways,” he says. “I just wouldn’t know enough; it would be too hard to learn; I wouldn’t have the time.”
Younger scientists often ask him about exploring multiple fields, Balasubramanian says. The advice he offers is to “have a central line where you have credibility, where you’ve established that you’re really, really good at what you do, and you can be trusted.” That gives you more latitude, he says.
After that, it’s just sheer discipline. “You’re going to have to wake up earlier than everybody else. You’re going to have to work longer days,” he says. “Otherwise, you know, everybody else is working hard too, and you’ll never be able to achieve the level of expertise and knowledge to be able to do things at that world-class level.”
Balasubramanian wants to see more interdisciplinary collaboration. “Each field trains its students with a certain body of techniques that has been found historically useful in that field,’ he says. “Very often, those techniques also have uses elsewhere, but they don’t know to apply it.”
Traversing borders can be helpful in producing new insights, Balasubramanian says. You can ask questions that people in the field won’t. You might experiment with new ideas or put two disjointed ideas together, he says. “If you’re coming from outside, you have the leeway to do all kinds of silly things. Sometimes, they’re not silly.”
Why not ask new questions and propose new answers? In the end, the data will tell you what’s true. “It gives me comfort to know how things tick.”
This post is adapted from a longer story in Penn Today. Read the full story here.
Balasubramanian is Cathy and Marc Lasry Professor in the Department of Physics and Astronomy in the Penn School of Arts and Sciences and is a member of the Penn Bioengineering Graduate Group. Read more stories featuring his research here.
Sometimes, nature’s smallest objects have the biggest impact. Take the quantum realm, which involves the building blocks of matter itself.
Quantum science aims to understand the behavior of matter and energy at the scale of atoms and subatomic particles. Because particles frequently defy human intuition at this scale, the field likely offers great, untapped potential to solve some of our most complex issues.
“Bringing ‘quantum superstars’ from academia and industry to a space where scientists of all levels could interact, exchange ideas and gain inspiration is just one way we can foster collaboration in advancing the field and exploring new possibilities,” says Lee Bassett, Associate Professor in Electrical and Systems Engineering (ESE) and Director of the Center for Quantum Information, Engineering, Science and Technology (QUIEST).
Established in June 2023, QUIEST hosted its first symposium, The Penn Forum on Quantum Systems (FoQuS), last month, which reached over 150 attendees and included keynote speakers from across the country and globe.
“The event was a wonderful success,” says Bassett. “External speakers appreciated being part of these discussions and seeing the exciting things happening at Penn. Penn faculty and students were thrilled to learn more about the state-of-the-art quantum research happening around the world in industry and in national labs.”
The forum’s goals were to connect researchers, raise awareness about regional, national and international efforts in quantum engineering and help guide research and education priorities for the QUIEST Center.
Touching on all four research domains of the Center (Materials for QUIEST, Quantum Devices, Quantum Systems and QUIEST Impact), the forum left attendees, including faculty as well as graduate, undergraduate and high school students, with new inspiration for future research.
Read the full story in Penn Engineering Today.
Dawn Bonnell, Henry Robinson Towne Professor in Materials Science and Engineering, Senior Vice Provost for Research, and member of the Penn Bioengineering Graduate Group, delivered opening remarks of FoQuS.
Nader Engheta (left) and Firooz Aflatouni swap ideas over cups of tea.
According to Chinese legend, the first cup of tea was an accident. Shennong, a mythical emperor, boiled a pot of water, only for the wind to add a handful of leaves.
Nader Engheta, H. Nedwill Ramsey Professor, regularly joins his colleague Firooz Aflatouni, associate professor and undergraduate chair in ESE, for a cup of tea in the latter’s office. “We talk about academic life,” says Engheta. “We talk about history, politics.” And, of course, science.
Engheta, who won the Benjamin Franklin Medal last year, is known for his groundbreaking contributions to the design of materials that interact with electromagnetic waves at tiny scales with unprecedented functionalities. More than a decade ago, the Department recruited Aflatouni, who specializes in the design of electronic and photonic chips, and Engheta became his mentor. “We come from different angles to the field of optics,” says Engheta.
Over tea, the two brew up new ideas. While perhaps not as directly inspired by teatime as James Watt, who famously experimented with kettles en route to inventing the steam engine, the pair nonetheless finds that ideas rise like the steam from their teacups. “It’s a pleasure to collaborate with Firooz,” says Engheta. “We love to see how we can bring our ideas together.”
Nader Engheta is H. Nedwill Ramsey Professor of Electrical and Systems Engineering at Penn Engineering, with secondary appointments in the departments of Bioengineering, Materials Science and Engineering, and Physics and Astronomy in the School of Arts & Sciences. Read more stories featuring Engheta in the BE Blog.
Computing at the speed of light may reduce the energy cost of training AI. (Narongrit Doungmanee via Getty Images)
Penn Engineers have developed a new chip that uses light waves, rather than electricity, to perform the complex math essential to training AI. The chip has the potential to radically accelerate the processing speed of computers while also reducing their energy consumption.
The silicon-photonic (SiPh) chip’s design is the first to bring together Benjamin Franklin Medal Laureate and H. Nedwill Ramsey Professor Nader Engheta’s pioneering research in manipulating materials at the nanoscale to perform mathematical computations using light — the fastest possible means of communication — with the SiPh platform, which uses silicon, the cheap, abundant element used to mass-produce computer chips.
The interaction of light waves with matter represents one possible avenue for developing computers that supersede the limitations of today’s chips, which are essentially based on the same principles as chips from the earliest days of the computing revolution in the 1960s.
In a paper in Nature Photonics, Engheta’s group, together with that of Firooz Aflatouni, Associate Professor in Electrical and Systems Engineering, describes the development of the new chip. “We decided to join forces,” says Engheta, leveraging the fact that Aflatouni’s research group has pioneered nanoscale silicon devices.
Their goal was to develop a platform for performing what is known as vector-matrix multiplication, a core mathematical operation in the development and function of neural networks, the computer architecture that powers today’s AI tools.
Nader Engheta is the H. Nedwill Ramsey Professor in Electrical and Systems Engineering, Bioengineering, Materials Science and Engineering, and in Physics and Astronomy.
NASA’s James Webb Space Telescope has produced the deepest and sharpest infrared image of the distant universe to date. Known as Webb’s First Deep Field, this image of galaxy cluster SMACS 0723 is rich with detail. Thousands of galaxies—including the faintest objects ever observed in the infrared—have appeared in Webb’s view for the first time. The image shows the galaxy cluster SMACS 0723 as it appeared 4.6 billion years ago. The combined mass of this galaxy cluster acts as a gravitational lens, magnifying much more distant galaxies behind it. Webb’s Near-Infra Red Cam has brought those distant galaxies into sharp focus—they have tiny, faint structures that have never been seen before, including star clusters and diffuse features. (Image: NASA, ESA, CSA, and STScI)
Could the universe be twice as old as current estimates put forward? Rajendra Gupta of the University of Ottawa recently published a paper suggesting just that. Gupta claims the universe may be around 26.7 billion years rather than the commonly accepted 13.8 billion. The news has generated many headlines as well as criticism from astronomers and the larger scientific community.
Penn Today met with professors Vijay Balasubramanian and Mark Devlin to discuss Gupta’s findings and better understand the rationale of these claims and how they fit in the broader context of problems astronomers are attempting to solve.
How do we know how old the universe actually is?
Balasubramanian: The universe is often reported to be 13.8 billion years old, but, truth be told, this is an amalgamation of various measurements that factor in different kinds of data involving the apparent ages of ‘stuff’ in the universe.
This stuff includes observable or ordinary matter like you, me, galaxies far and near, stars, radiation, and the planets, then dark matter—the sort of matter that doesn’t interact with light and which makes up about 27% of the universe—and finally, dark energy, which makes up a massive chunk of the universe, around 68%, and is what we believe is causing the universe to expand.
And so, we take as much information as we can about the stuff and build what we call a consensus model of the universe, essentially a line of best fit. We call the model the Lambda Cold Dark Matter (ΛCDM).
Lambda represents the cosmological constant, which is linked to dark energy, namely how it drives the expansion of the universe according to Einstein’s theory of general relativity. In this framework, how matter and energy behave in the universe determines the geometry of spacetime, which in turn influences how matter and energy move throughout the cosmos. Including this cosmological constant, Lambda, allows for an explanation of a universe that expands at an accelerating rate, which is consistent with our observations.
Now, the Cold Dark Matter part represents a hypothetical form of dark matter. ‘Dark’ here means that it neither interacts with nor emits light, so it’s very hard to detect. ‘Cold’ refers to the fact that its particles move slowly because when things cool down their components move less, whereas when they heat up the components get excited and move around more relative to the speed of light.
So, when you consider the early formation of the universe, this ‘slowness’ influences the formation of structures in the universe like galaxies and clusters of galaxies, in that smaller structures like the galaxies form before the larger ones, the clusters.
Devlin: And then taking a step back, the way cosmology works and pieces how old things are is that we look at the way the universe looks today, how all the structures are arranged within it, and we compare it to how it used to be with a set of cosmological parameters like Cosmic Microwave Background (CMB) radiation, the afterglow of the Big Bang, and the oldest known source of electromagnetic radiation, or light. We also refer to it as the baby picture of the universe because it offers us a glimpse of what it looked like at 380,000 years old, long before stars and galaxies were formed.
And what we know about the physical nature of the universe from the CMB is that it was something really smooth, dense, and hot. And as it continued to expand and cool, the density started to vary, and these variations became the seeds for the formation of cosmic structures.
The denser regions of the universe began to collapse under their own gravity, forming the first stars, galaxies, and clusters of galaxies. So, this is why, when we look at the universe today, we see this massive cosmic web of galaxies and clusters separated by vast voids. This process of structure formation is still ongoing.
And, so, the ΛCDM model suggests that the primary driver of this structure formation was dark matter, which exerts gravity and which began to clump together soon after the Big Bang. These clumps of dark matter attracted the ordinary matter, forming the seeds of galaxies and larger cosmic structures.
So, with models like the ΛCDM and the knowledge of how fast light travels, we can add bits of information, or parameters, and we have from things like the CMB and other sources of light in our universe, like the ones we get from other distant galaxies, and we see this roadmap for the universe that gives us it’s likely age. Which we think is somewhere in the ballpark of 13.8 billion years.
Vijay Balasubramanian is the Cathy and Marc Lasry Professor in the Department of Physics and Astronomy in the School of Arts & Sciences at the University of Pennsylvania. He is a member of the Penn Bioengineering Graduate Group.
Mark Devlin is the Reese W. Flower Professor of Astronomy and Astrophysics in the Department of Physics and Astronomy in the School of Arts & Sciences at Penn.
Nader Engheta was puzzled when he got a call from the psychology department about a fish. In the early 1990s, Engheta, a newly minted associate professor of electrical engineering in Penn’s School of Engineering and Applied Science, was a respected expert in radio wave technologies. But in recent years, his work had been expanding into subjects at once more eccentric and fundamental.
Nader Engheta was puzzled when he got a call from the psychology department about a fish.
In the early 1990s, Engheta, a newly minted associate professor of electrical engineering in Penn’s School of Engineering and Applied Science, was a respected expert in radio wave technologies. But in recent years, his work had been expanding into subjects at once more eccentric and fundamental.
Engheta’s interest in electromagnetic waves was not limited to radio frequencies, as a spate of fresh publications could attest. Some studies investigated a range of wave interactions with a class of matter known as a “chiral media,” materials with molecular configurations that exhibit qualities of left or right “handedness.” Others established practical electromagnetic applications for a bewildering branch of mathematics called “fractional calculus,” an area with the same Newtonian roots as calculus proper but a premise as eyebrow-raising as the suggestion a family might literally include two-and-a-half children.
Electromagnetic waves are organized on a spectrum of wavelengths. On the shorter end of the spectrum are high-energy waves, such as X-rays. In the middle, there is the limited range we see as visible light. And on the longer end are the lower-energy regimes of radio and heat.
Researchers tend to focus on one kind of wave or one section of the spectrum, exploring quirks and functions unique to each. But all waves, electromagnetic or not, share the same characteristics: They consist of a repeating pattern with a certain height (amplitude), rate of vibration (frequency), and distance between peaks (wavelength). These qualities can define a laser beam, a broadcasting voice, a wind-swept lake, or a violin string.
Engheta has never been the kind of scholar to limit the scope of his curiosity to a single field of research. He is interested in waves, and his fascination lies equally in the physics that determine wave behavior and the experimental technologies that push the boundaries of those laws.
So, when Edward Pugh, a mathematical psychologist studying the physiology of visual perception, explained that green sunfish might possess an evolutionary advantage for seeing underwater, Engheta listened.
Soon, the two Penn professors were pouring over microscope images of green sunfish retinas.
Read Devorah Fischler’s full story about Nader Engheta and watch an accompanying video at Penn Today.
Nader Engheta is H. Nedwill Ramsey Professor of Electrical and Systems Engineering at Penn Engineering, with secondary appointments in the departments of Bioengineering, Materials Science and Engineering, and Physics and Astronomy in the School of Arts & Sciences.
(Left to Right) Vijay Kumar, Nemirovsky Family Dean of Penn Engineering, Nader Engheta, H. Nedwill Ramsey Professor in Electrical and Systems Engineering, and Michele Marcolongo, Drosdick Endowed Dean of Villanova University’s College of Engineering
On April 26, scholars from all over the world gathered at Villanova University to celebrate extraordinary innovation in the physics and technology of light.
The symposium, titled “Sculpting Waves with Complex Materials,” explored the richness and breadth of Engheta’s impact.
In a glass-paneled lecture hall nestled between flowering dogwoods and limber pines, speakers attested to Engheta’s technical acumen and intellectual creativity, describing his pathbreaking work in light-matter interaction.
Andrea Alù, Distinguished Professor at the City University of New York, Einstein Professor of Physics at the Graduate Center, CUNY and former Penn Engineering postdoctoral fellow, cited Engheta as “one of the original pioneers of the field of complex electromagnetic structures and modern metamaterials,” and the “father” of four influential fields: analog computing with metamaterials, plasmonic cloaking, non-zero-index metamaterials and optical nanocircuits.
Two faculty affiliated with the Department of Bioengineering at the University of Pennsylvania have been elected to the American Academy of Arts & Sciences. They join nearly 270 new members honored in 2023, recognized for their excellence, innovation, leadership, and broad array of accomplishments.
Nader Engheta, the H. Nedwill Ramsey Professor.
Nader Engheta is the H. Nedwill Ramsey Professor, with affiliations in the departments of Electrical and Systems Engineering (primary appointment), Bioengineering (secondary appointment) and Materials Science and Engineering (secondary appointment) in the School of Engineering and Applied Science; and Physics and Astronomy (secondary appointment) in the School of Arts & Sciences. His current research activities span a broad range of areas including optics, photonics, metamaterials, electrodynamics, microwaves, nano-optics, graphene photonics, imaging and sensing inspired by eyes of animal species, microwave and optical antennas, and physics and engineering of fields and waves. He has received numerous awards for his research, including the 2023 Benjamin Franklin Medal in Electrical Engineering, the 2020 Isaac Newton Medal and Prize from the Institute of Physics (U.K.), the 2020 Max Born Award from OPTICA (formerly OSA), induction to the Canadian Academy of Engineering as an International Fellow (2019), U.S. National Academy of Inventors (2015), and the Ellis Island Medal of Honor from the Ellis Island Honors Society (2019). He joins four other Penn faculty elected to the Academy this year.
Read the announcement and the full list of Penn electees in Penn Today.
Susan Margulies, Ph.D. (Photo: Jack Kearse)
Susan Margulies, Professor in the Wallace H. Coulter Department of Biomedical Engineering in the College of Engineering at Georgia Tech, was also elected. Margulies is both Professor Emeritus in Penn Bioengineering and an alumna of the program, having earned her Ph.D. with the department in 1987. Margulies is an expert in pediatric traumatic brain injury and lung injury. She previously served as Chair of Biomedical Engineering at Georgia Tech/Emory University and in 2021 became the first biomedical engineer selected to lead the National Science Foundation’s (NSF) Directorate of Engineering.
Read the announcement of Margulies’ elected to the Academy at Georgia Tech.
