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.
The NSF AIRFoundry will accelerate RNA research using the power of AI and educate the next generation of RNA researchers. (DesignCells via Getty Images)
In a typical foundry, raw materials like steel and copper are melted down and poured into molds to assume new shapes and functions. The U.S. National Science Foundation Artificial Intelligence-driven RNA Foundry (NSF AIRFoundry), led by the University of Pennsylvania and the University of Puerto Rico and supported by an $18-million, six-year grant, will serve much the same purpose, only instead of smithing metal, the “BioFoundry” will create molecules and nanoparticles.
NSF AIRFoundry is one of five newly created BioFoundries, each of which will have a different focus. Bringing together researchers from Penn Engineering, Penn Medicine’s Institute for RNA Innovation, the University of Puerto Rico–Mayagüez (UPR-M), Drexel University, the Children’s Hospital of Philadelphia (CHOP) and InfiniFluidics, the facility, which will be physically located in West Philadelphia and at UPR-M, will focus on ribonucleic acid (RNA), the tiny molecule essential to genetic expression and protein synthesis that played a key role in the COVID-19 vaccines and saved tens of millions of lives.
The facility will use AI to design, optimize and synthesize RNA and delivery vehicles by augmenting human expertise, enabling rapid iterative experimentation, and providing predictive models and automated workflows to accelerate discovery and innovation.
“With NSF AIRFoundry, we are creating a hub for innovation in RNA technology that will empower scientists to tackle some of the world’s biggest challenges, from health care to environmental sustainability,” says Daeyeon Lee, Russell Pearce and Elizabeth Crimian Heuer Professor in Chemical and Biomolecular Engineering in Penn Engineering and NSF AIRFoundry’s director.
“Our goal is to make cutting-edge RNA research accessible to a broad scientific community beyond the health care sector, accelerating basic research and discoveries that can lead to new treatments, improved crops and more resilient ecosystems,” adds Nobel laureate Drew Weissman, Roberts Family Professor in Vaccine Research in Penn Medicine, Director of the Penn Institute for RNA Innovation and NSF AIRFoundry’s senior associate director.
The facility will catalyze new innovations in the field by leveraging artificial intelligence (AI). AI has already shown great promise in drug discovery, poring over vast amounts of data to find hidden patterns. “By integrating artificial intelligence and advanced manufacturing techniques, the NSF AIRFoundry will revolutionize how we design and produce RNA-based solutions,” says David Issadore, Professor in Bioengineering and in Electrical and Systems Engineering at Penn Engineering and the facility’s associate director of research coordination.
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.”
BE’s award-winning team, Epilog, at the 2024 Senior Design Awards.
How do you make robotics kits affordable for children in low-income countries? Speed up the manufacturing of organs-on-a-chip? Lower the environmental impact of condiments in restaurants?
If you’re a senior at Penn Engineering, the answer is to team up with your peers in the Senior Design Project Competition, which every year draws interdisciplinary groups from across the School’s six majors to solve real-world problems. Championed by the late Walter Korn (EE’57, GEE’68), a past president of the Engineering Alumni Society (EAS), Senior Design also invites alumni back to campus to evaluate the seniors’ year-long capstone projects.
Since the program started nearly two decades ago, hundreds of alumni have shared centuries’ worth of their collective experience with soon-to-be-minted graduates in the form of constructive feedback. “Senior Design is really one of the best days at Penn Engineering,” says Bradley Richards (C’92, LPS’17), Director of Alumni Relations, who manages the program. “Faculty advisors work with students all year long to bring out the best in each group’s efforts, and the results speak for themselves.”
This year, three student teams from each of Penn Engineering’s six departments — Bioengineering (BE), Chemical and Biomolecular Engineering (CBE), Computer and Information Science (CIS), Electrical and Systems Engineering (ESE), Materials Science and Engineering (MSE), and Mechanical Engineering and Applied Mechanics (MEAM) — presented their work to more than 60 alumni in person and online.
Judges’ Choice Award
The Judges’ Choice Award, which recognizes overall excellence, went to ESE’s VivoDisk, which developed a novel machine to manufacture organs-on-a-chip for Vivodyne, a startup launched by Dan Huh, Associate Professor in BE.
As one of the team members, Akash Chauhan (ENG’24), learned while interning for Vivodyne, assembling the stacks of organs-on-a-chip, which are collections of plastic plates containing cells that simulate organs for preclinical drug testing, is extremely finicky and time consuming.
By developing a machine that could automatically align the plates with high precision using computer vision and AI, the team reduced the disks’ manufacturing time and expense, leading Vivodyne to adopt the device for commercial use, accelerating the process of drug discovery. VivoDisk’s team members included Chauhan; Angela Rodriguez (ENG’24), Aliris Tang (ENG’24, W’24), Dagny Lott (ENG’24), Simone Kwee (ENG’24) and Vraj Satashia (ENG’24, GEN’25) and was advised by Sid Deliwala, Alfred Moore Senior Fellow and Director of Lab Programs in ESE, and Jan Van der Spiegel, Professor in ESE.
Technology and Innovation Award
One of the greatest challenges for children with epilepsy is status epilepticus, an abnormal type of long-lasting seizure that is hard to distinguish from typical seizures and that has a mortality rate of 30%. There is currently no way to perform a test for status epilepticus at home, meaning that children suspected of having the condition must be rushed to the hospital for an electroencephalogram.
Epilog, a team from BE, developed a novel, wearable headset that analyzes brainwaves to accurately determine whether or not a child suffering a seizure is actually suffering from status epilepticus. The team, composed of Rohan Chhaya (ENG’24, GEN’24), Carly Flynn (ENG’24), Elena Grajales (ENG’24), Priya Shah (ENG’24, GEN’25) and Doris Xu (ENG’24) and advised by Erin Berlew, Research Scientist in the Department of Orthopaedic Surgery and Lecturer in BE, carefully validated the device’s accuracy.
The judges recognized Epilog’s technological expertise, which ran the gamut from software to hardware, including a custom app to work with the device and carefully considered features like electrodes whose position can be adjusted to accommodate a child’s growth over time.
How do we measure chaos and why would we want to? Together, Penn engineers Dani S. Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering, and postdoctoral researcher Kieran Murphy leverage the power of machine learning to better understand chaotic systems, opening doors for new information analyses in both theoretical modeling and real-world scenarios.
Humans have been trying to understand and predict chaotic systems such as weather patterns, the movement of planets and population ecology for thousands of years. While our models have continued to improve over time, there will always remain a barrier to perfect prediction. That’s because these systems are inherently chaotic. Not in the sense that blue skies and sunshine can turn into thunderstorms and torrential downpours in a second, although that does happen, but in the sense that mathematically, weather patterns and other chaotic systems are governed by physics with nonlinear characteristics.
“This nonlinearity is fundamental to chaotic systems,” says Murphy. “Unlike linear systems, where the information you start with to predict what will happen at timepoints in the future stays consistent over time, information in nonlinear systems can be both lost and generated through time.”
Like a game of telephone where information from the original source gets lost as it travels from person to person while new words and phrases are added to fill in the blanks, outcomes in chaotic systems become harder to predict as time passes. This information decay thwarts our best efforts to accurately forecast the weather more than a few days out.
“You could put millions of probes in the atmosphere to measure wind speed, temperature and precipitation, but you cannot measure every single atom in the system,” says Murphy. “You must have some amount of uncertainty, which will then grow, and grow quickly. So while a prediction for the weather in a few hours might be fairly accurate, that growth in uncertainty over time makes it impossible to predict the weather a month from now.”
In their recent paper published in Physical Review Letters, Murphy and Bassett applied machine learning to classic models of chaos, physicists’ reproductions of chaotic systems that do not contain any external noise or modeling imperfections, to design a near-perfect measurement of chaotic systems to one day improve our understanding of systems including weather patterns.
“These controlled systems are testbeds for our experiments,” says Murphy. “They allow us to compare with theoretical predictions and carefully evaluate our method before moving to real-world systems where things are messy and much less is known. Eventually, our goal is to make ‘information maps’ of real-world systems, indicating where information is created and identifying what pieces of information in a sea of seemingly random data are important.”
Team Current Care (Andrew Lee, Antranig Baghdassarian, Johnson Liu, Leah Lackey, Brianna Leung, and Justin Liu), took home the $3,000 Grand Prize in the Cornell Hackathon.
Brianna Leung, a rising senior majoring in Bioengineering and minoring in Neuroscience and Healthcare Management at the University of Pennsylvania, led a diverse team of student scientists and engineers to resounding success at the 2024 Cornell Health Tech Hackathon, where the team won the $3,000 Grand Prize.
Held in March 2024 on Cornell’s campus in New York City, the event brought together students from 29 different universities for a weekend of finding “hacks” to patient wellness and healthcare issues inspired by the theme of “patient safety.”
ADAPT members enjoy a pancake-making marathon in preparation for their pancake sale.
Leung serves as President of Penn Assistive Devices and Prosthetic Technologies (ADAPT), a medical-device project club whose members pursue personal projects, community partnerships and national design competitions. Penn ADAPT’s activities range from designing, building and improving assistive medical devices for conditions such as cerebral palsy and limb loss, to community engagement activities like their semesterly 3D-printed pancake sale.
In her role, Leung has increased the program’s hackathon participation to give club members greater exposure to fast-paced, competition-based design. She also leads the HMS School project, which develops and manufactures switch interfaces for children with cerebral palsy, enabling these students to interact with computers.
Leung’s passion for medical devices extends to her academic research. As a member of the robotics lab of Cynthia Sung, Gabel Family Term Assistant Professor in Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering, Leung characterizes origami patterns for energy-saving applications in the heart and in facial reconstruction. Leung has also served as Vice President External for the Penn Lions and Vice President of Member Engagement for the Wharton Undergraduate Healthcare Club, and belongs to the Phi Gamma Nu professional business fraternity.
ADAPT members working on medical devices.
For the Cornell Hackathon, Leung’s team developed a prototype for Current Care, a closed-loop device to prevent pressure ulcers through electrical muscle stimulation. Pressure ulcers, often called bed sores, result from prolonged pressure, which often occurs during extended hospitalization or in patients who are bedridden. This condition is exacerbated by understaffing and strained resources, and can create an extra burden on hospitals, patients and healthcare workers. The U.S. Department of Health and Human Services estimates that pressure ulcers cost the U.S. healthcare system approximately $9.1 billion to $11.6 billion per year.
Current Care is designed to deliver electrical stimulation, which increases blood flow to affected body parts. Conceptualizing and designing complex devices on short notice is the nature of a hackathon, so the team focused their efforts on creating proof-of-concept prototypes for all the different sensors required for the device, as well as providing the judges with on-screen read-outs to demonstrate the logic and hypothetical inputs for the device.
For their design, the team was awarded the $3,000 Grand Prize in the Cornell Hackathon. In addition to Leung, the team consisted of Johnson Liu (Cornell ECE & MSE’26); Antranig Baghdassarian (Cornell BME’27); Andrew Lee (Weill Cornell M.D.’25); Leah Lackey (Cornell ECE Ph.D.’28); and Justin Liu (Northeastern CS’27).
In choosing a project, Leung was inspired by her late grandmother’s experiences. “My role on the team largely consisted of coordinating and leading aspects of its development as needed. I also ultimately presented our idea to the judges,” she says. “This was actually all of my teammates’ first hackathon, so it was really exciting to serve a new role (considering it was actually only my second hackathon!). I had a lot of fun working with them, and we have actually been meeting regularly since the event to continue to work on the project. We had a range of expertise and experience on our team, and I deeply appreciate their hard work and enthusiasm for a project that means so much to me.”
Having found success at the Cornell hackathon, the team is discussing next steps for Current Care. “Our team is still very motivated to continue working on the project, and we’ve been speaking with professors across all of our schools to discuss feasibility and design plans moving forward,” says Leung.
Several other projects developed by Penn ADAPT members were recognized in the Cornell Hackathon:
ADAPT members and Hackathon participants, left to right: Brianna Leung, Rebecca Wang, Claire Zhang, Amy Luo, Mariam Rizvi, Natey Kim, Joe Kojima. Also in attendance but not pictured: Suhani Patel, Harita Trivedi, Dwight Koyner.
Claire Zhang, a sophomore studying Bioengineering and Biology in the VIPER program, was a member and presenter for team CEDAR (winner of Most Innovative/2nd Place), a portable ultrasound imaging device used to monitor carotid artery stenosis development in rural areas.
Natey Kim, a sophomore in Bioengineering, was a member and presenter for team HMSS (finalist), a low-cost digital solution for forecasting infections in hospitals.
Rebecca Wang, a sophomore in Bioengineering and Social Chair of Penn ADAPT, was a member of Team Femnostics (winner of Most Market Ready/4th Place) which developed QuickSense, an all-in-one diagnostic tool that streamlines testing for a handful of the most common vaginal disease infections simultaneously.
Mariam Rizvi, a sophomore in Computational Biology, was a member of team IPVision (winner of Most Potential Impact/5th Place), an application programming interface (or API) that integrates into electronic health records such as Epic, leveraging AI to detect intimate partner violence cases and provide personalized treatment in acute-care settings.
Suhani Patel and Dwight Koyner worked with team RealAIs, which developed a full-stack multi-platform application using React Native and Vertex AI on the Google Cloud Platform (GCP). Patel, a sophomore double majoring in Bioengineering and Computer and Information Science in Penn Engineering, serves as ADAPT’s treasurer, while Koyner is a first-year M&T student studying Business and Systems Engineering in Penn Engineering and Wharton.
Team Femnostics from left to right: Antonia Li, Bhavishya Agarwal, Urmila Sehrawat, Rebecca Wang, Justin Xiang, and Edward Kim.Team IPVision from left to right: Elizabeth Madamidola, Keshika Gopinathan, Emily L. Leventhal, Mariam Rizvi, Raquel Castromonte, and Lina ChihoubTeam Cedar from left to right: Claire Zhang, Ethan Tse, Danny Nguyen, Allen Dinh, and Reem UllayTeam RealAIs from left to right: Rishi Shah, Suhani Patel, Saanvi Mehra, Dwight Koyner, Chimdi Ejiogu, and Garrett Breslin
Learn more about Penn ADAPT here and follow their Instagram.
Read more about the 2024 Cornell Tech Hackathon in the Cornell Chronicle.
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.
René Vidal, at the podium, introduces the event “ChatGPT turns one: How is generative AI reshaping science?” Bhuvnesh Jain, left at the table, moderated the discussion with Sudeep Bhatia, Konrad Kording, Andrew Zahrt, and Nick Pangakis.
As a neuroscientist surveying the landscape of generative AI—artificial intelligence capable of generating text, images, or other media—Konrad Kording cites two potential directions forward: One is the “weird future” of political use and manipulation, and the other is the “power tool direction,” where people use ChatGPT to get information as they would use a drill to build furniture.
“I’m not sure which of those two directions we’re going but I think a lot of the AI people are working to move us into the power tool direction,” says Kording, a Penn Integrates Knowledge (PIK) University professor with appointments in the Perelman School of Medicine and School of Engineering and Applied Science. Reflecting on how generative AI is shifting the paradigm of science as a discipline, Kording said he thinks “it will push science as a whole into a much more collaborative direction,” though he has concerns about ChatGPT’s blind spots.
Kording joined three University of Pennsylvania researchers from the chemistry, political science, and psychology departments sharing their perspectives in the recent panel “ChatGPT turns one: How is generative AI reshaping science?” PIK Professor René Vidal opened the event, which was hosted by the School of Arts & Sciences’ Data Driven Discovery Initiative (DDDI), and Bhuvnesh Jain, physics and astronomy professor and co-faculty director of DDDI, moderated the discussion.
“Generative AI is moving so rapidly that even if it’s a snapshot, it will be very interesting for all of us to get that snapshot from these wonderful experts,” Jain said. OpenAI launched ChatGPT, a large language model (LLM)-based chatbot, on Nov. 30, 2022, and it rapidly ascended to ubiquity in news reports, faculty discussions, and research papers. Colin Twomey, interim executive director of DDDI, told Penn Today that it’s an open question as to how it will change the landscape of scientific research, and the` idea of the event was to solicit colleagues’ opinions on interesting directions in their fields.
Konrad Paul Kording is Nathan Francis Mossell University Professor in Bioengineering and Computer and Information Science in Penn Engineering and in Neuroscience in the Perelman School of Medicine.
