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.
Artist-in-residence and visiting scholar Rebecca Kamen has blended AI and art to produce animated illustrations representing how a dyslexic brain interprets information.
Communicating thoughts with words is considered a uniquely human evolutionary adaptation known as language processing. Fundamentally, it is an information exchange, a lot like data transfer between devices, but one riddled with discrete layers of complexity, as the ways in which our brains interpret and express ideas differ from person to person.
Learning challenges such as dyslexia are underpinned by these differences in language processing and can be characterized by difficulty learning and decoding information from written text.
Artist-in-residence in Penn’s Department of Physics and Astronomy Rebecca Kamen has explored her personal relationship with dyslexia and information exchange to produce works that reflect elements of both her creative process and understanding of language. Kamen unveiled her latest exhibit at Arion Press Gallery in San Francisco, where nine artists with dyslexia were invited to produce imaginative interpretations of learning and experiencing language.
The artists were presented with several prompts in varying formats, including books, words, poems, quotes, articles, and even a single letter, and tasked with creating a dyslexic dictionary: an exploration of the ways in which their dyslexia empowered them to engage in information exchange in unique ways.
“[For the exhibit], each artist selected a word representing the way they learn, and mine was ‘lens,’” explains Kamen. “It’s a word that captures how being dyslexic provides me with a unique perspective for viewing and interacting with the world.”
From an early age, Kamen enjoyed learning about the natural sciences and was excited about the process of discovery. She struggled, however, with reading at school, which initially presented an obstacle to achieving her dreams of becoming a teacher. “I had a difficult time getting into college,” says Kamen. “When I graduated high school, the word ‘dyslexia’ didn’t really exist, so I assumed everyone struggled with reading.”
Kamen was diagnosed with dyslexia well into her tenure as a professor. “Most dyslexic people face challenges that may go unnoticed by others,” she says, “but they usually find creative ways to overcome them.”
This perspective on seeing and experiencing the world through the lens of dyslexia not only informed Kamen’s latest work for the exhibition “Dyslexic Dictionary,” but also showcased her background in merging art and science. For decades, Kamen’s work has investigated the intersection of the two, creating distinct ways of exploring new relationships and similarities.
“Artists and scientists are curious creatures always looking for patterns,” explains Kamen. “And that’s because patterns communicate larger insights about the world around us.”
The researchers studied different information-seeking approaches by monitoring how participants explore Wikipedia pages and categorically related these to two ideas rooted in philosophical understandings of learning: a “busybody,” who typically jumps between diverse ideas and collects loosely connected information; and a more purpose-driven “hunter,” who systematically ties in closely related concepts to fill their knowledge gaps.
They used these classifications to inform their computational model, the knowledge network. This uses text and context to determine the degree of relatedness between the Wikipedia pages and their content—represented by dots connected with lines of varying thickness to illustrate the strength of association.
In an adaption of the knowledge network, Kamen was classified as a dancer, an archetype elaborated on in an accompanying review paper by Dale Zhou, a Ph.D. candidate in Bassett’s Complex Systems Lab, who had also collaborated with Kamen on “Reveal.”
“The dancer can be described as an individual that breaks away from the traditional pathways of investigation,” says Zhou. “Someone who takes leaps of creative imagination and in the process, produces new concepts and radically remodels knowledge networks.”
Dani Smith Bassett is J. Peter Skirkanich Professor in Bioengineering with secondary appointments in the Departments of Physics & Astronomy, Electrical & Systems Engineering, Neurology, and Psychiatry.
David Lydon-Staley is an Assistant Professor in the Annenberg School for Communications and Bioengineering and is an alumnus of the Bassett Lab.
University of Pennsylvania scientist Nader Engheta has been selected as a 2023 recipient of the Benjamin Franklin Medal, one of the world’s oldest science and technology awards. The laureates will be honored on April 27 at a ceremony at the Franklin Institute in Philadelphia.
Engheta, H. Nedwill Ramsey Professor in Electrical and Systems Engineering, is among nine outstanding individuals recognized with Benjamin Franklin Medals this year for their achievements in extraordinary scientific, engineering and business leadership.
“As a scientist and a Philadelphian, I am deeply honored and humbled to receive the Franklin Medal. It is the highest compliment to receive an award whose past recipients include some of my scientific heroes such as Albert Einstein, Nikola Tesla, Alexander Graham Bell, and Max Planck. I am very thankful to the Franklin Institute for bestowing this honor upon me.”
Larry Dubinski, President and CEO of The Franklin Institute, says, “We are proud to continue The Franklin Institute’s longtime legacy of recognizing individuals for their contributions to humanity. These extraordinary advancements in areas of such importance as social equity, sustainability, and safety are significantly moving the needle in the direction of positive change and therefore laying the groundwork for a remarkable future.”
The 2023 Benjamin Franklin Medal in Electrical Engineering goes to Engheta for his transformative innovations in engineering novel materials that interact with electromagnetic waves in unprecedented ways, with broad applications in ultrafast computing and communication technologies.
“Professor Engheta’s pioneering work in metamaterials and nano-optics points the way to new and truly revolutionary computing capabilities in the future,” says University of Pennsylvania President Liz Magill. “Penn inaugurated the age of computers by creating the world’s first programmable digital computer in 1945. Professor Engheta’s work continues this tradition of groundbreaking research and discovery that will transform tomorrow. We are thrilled to see him receive the recognition of the Benjamin Franklin Medal.”
Engheta founded the field of optical nanocircuits (“optical metatronics”), which merges nanoelectronics and nanophotonics. He is also known for establishing and& developing the field of near-zero-index optics and epsilon-near-zero (ENZ) materials with near-zero electric permittivity. Through his work he has opened many new frontiers, including optical computation at the nanoscale and scattering control for cloaking and transparency. His work has far-reaching implications in various branches of electrical engineering, materials science, optics, microwaves, and quantum electrodynamics.
“This award recognizes Dr. Engheta’s trailblazing advances in engineering and physics,” says Vijay Kumar, Nemirovsky Family Dean of Penn Engineering.“ The swift and sustainable technologies his research in metamaterials and metatronics offers the world are the result of a lifelong commitment to scientific curiosity. For over 35 years, Nader Engheta has personified Penn Engineering’s mission of inventing the future.”
Nader Engheta is the H. Nedwill Ramsey Professor in the Departments of Electrical and Systems Engineering and Bioengineering in the School of Engineering and Applied Science and professor of physics and astronomy in the School of Arts & Sciences at the University of Pennsylvania.
Penn Engineering’s newly established ASSET Center aims to make AI-enabled systems more “safe, explainable and trustworthy” by studying the fundamentals of the artificial neural networks that organize and interpret data to solve problems.
ASSET’s first funding collaboration is with Penn’s Perelman School of Medicine (PSOM) and the Penn Institute for Biomedical Informatics (IBI). Together, they have launched a series of seed grants that will fund research at the intersection of AI and healthcare.
Teams featuring faculty members from Penn Engineering, Penn Medicine and the Wharton School applied for these grants, to be funded annually at $100,000. A committee consisting of faculty from both Penn Engineering and PSOM evaluated 18 applications and judged the proposals based on clinical relevance, AI foundations and potential for impact.
Artificial intelligence and machine learning promise to revolutionize nearly every field, sifting through massive amounts of data to find insights that humans would miss, making faster and more accurate decisions and predictions as a result.
Applying those insights to healthcare could yield life-saving benefits. For example, AI-enabled systems could analyze medical imaging for hard-to-spot tumors, collate multiple streams of disparate patient information for faster diagnoses or more accurately predict the course of disease.
Given the stakes, however, understanding exactly how these technologies arrive at their conclusions is critical. Doctors, nurses and other healthcare providers won’t use such technologies if they don’t trust that their internal logic is sound.
“We are developing techniques that will allow AI-based decision systems to provide both quantifiable guarantees and explanations of their predictions,” says Rajeev Alur, Zisman Family Professor in Computer and Information Science and Director of the ASSET Center. “Transparency and accuracy are key.”
“Development of explainable and trustworthy AI is critical for adoption in the practice of medicine,” adds Marylyn Ritchie, Professor of Genetics and Director of the Penn Institute for Biomedical Informatics. “We are thrilled about this partnership between ASSET and IBI to fund these innovative and exciting projects.”
Seven projects were selected in the inaugural class, including projects from Dani S. Bassett, J. Peter Skirkanich Professor in the Departments of Bioengineering, Electrical and Systems Engineering, Physics & Astronomy, Neurology, and Psychiatry, and several members of the Penn Bioengineering Graduate Group: Despina Kontos, Matthew J. Wilson Professor of Research Radiology II, Department of Radiology, Penn Medicine and Lyle Ungar, Professor, Department of Computer and Information Science, Penn Engineering; Spyridon Bakas, Assistant Professor, Departments of Pathology and Laboratory Medicine and Radiology, Penn Medicine; and Walter R. Witschey, Associate Professor, Department of Radiology, Penn Medicine.
Optimizing clinical monitoring for delivery room resuscitation using novel interpretable AI
Elizabeth Foglia, Associate Professor, Department of Pediatrics, Penn Medicine and the Children’s Hospital of Philadelphia
Dani S. Bassett, J. Peter Skirkanich Professor, Departments of Bioengineering and Electrical and Systems Engineering, Penn Engineering
This project will apply a novel interpretable machine learning approach, known as the Distributed Information Bottleneck, to solve pressing problems in identifying and displaying critical information during time-sensitive clinical encounters. This project will develop a framework for the optimal integration of information from multiple physiologic measures that are continuously monitored during delivery room resuscitation. The team’s immediate goal is to detect and display key target respiratory parameters during delivery room resuscitation to prevent acute and chronic lung injury for preterm infants. Because this approach is generalizable to any setting in which complex relations between information-rich variables are predictive of health outcomes, the project will lay the groundwork for future applications to other clinical scenarios.
The Heilmeier Award honors a Penn Engineering faculty member whose work is scientifically meritorious and has high technological impact and visibility. It is named for the late George H. Heilmeier, a Penn Engineering alumnus and member of the School’s Board of Advisors, whose technological contributions include the development of liquid crystal displays and whose honors include the National Medal of Science and Kyoto Prize.
Bassett, who also holds appointments in Physics & Astronomy in Penn Arts & Sciences and in Neurology and Psychiatry in the Perelman School of Medicine, is a pioneer in the field of network neuroscience, an emerging subfield which incorporates elements of mathematics, physics, biology and systems engineering to better understand how the overall shape of connections between individual neurons influences cognitive traits. They lead the Complex Systems lab, which tackles problems at the intersection of science, engineering and medicine using systems-level approaches, exploring fields such as curiosity, dynamic networks in neuroscience, and psychiatric disease.
Bassett will deliver the 2022-23 Heilmeier Award Lecture in Spring 2023.
With appointments in the Departments of Bioengineering and Electrical and Systems Engineering, as well as the Department of Physics and Astronomy in Penn Arts & Science, and the Departments of Neuroscience and Psychiatry in Penn Perelman’s School of Medicine, Dani S. Bassett is no stranger to following the thread of an idea, no matter where it might lead.
Those wide-ranging fields and disciplines orbit around an appropriate central question: how does the tangle of neurons in our brains wire itself up to learn new things? Bassett, J. Peter Skirkanich Professor and director of the Complex Systems Lab, studies the relationship between the shape of those networks of neurons and the brain’s abilities, especially the way the shape of the network grows and changes with the addition of new knowledge.
To get at the fundamentals of the question of curiosity, Bassett needed to draw on even more disciplines. Fortunately, they didn’t have to look far; Bassett’s identical twin is Perry Zurn, a professor of philosophy at American University, and the two have investigated the many different ways a person can exhibit curiosity.
Bassett and Zurn have now published a new book on the subject. In Curious Minds: The Power of Connection, the twins draw on their previous research, as well as an expansive network of ideas from philosophy, history, education and art.
“It wasn’t clear at the beginning of our careers that we would even ever have a chance to write a book together because our areas were so wildly different,” Bassett says – but then, as postgraduates, Zurn was studying the philosophy of curiosity while Bassett was working on the neuroscience of learning. “And so that’s when we started talking. That talking led to seven years of doing research together,” Bassett says. “This book is a culmination of that.”
How exactly do philosophy and neuroscience complement each other? It all starts with the book’s first, and most deceptively simple question: what is curiosity? “Several investigators in science have underscored that perhaps the field isn’t even ready to define curiosity and how it’s different from other cognitive processes,” says Bassett. The ambiguity in the neuroscience literature motivated Bassett to turn to philosophy, “where there are really rich historical definitions and styles and subtypes that we can then put back into neuroscience and ask: ‘Can we see these in the brain?’”
Last month, the second annual Women in Data Science (WiDS) @ Penn Conference virtually gathered nearly 500 registrants to participate in a week’s worth of academic and industry talks, live speaker Q&A sessions, and networking opportunities.
Following welcoming remarks from Erika James, Dean of the Wharton School, and Vijay Kumar, Nemirovsky Family Dean of Penn Engineering, the conference began with a keynote address from President of Microsoft US and Wharton alumna Kate Johnson.
Conference sessions continued throughout the week, featuring panels of academic data scientists from around Penn and beyond, industry leaders from IKEA Digital, Facebook and Poshmark, and lightning talks from students speakers who presented their data science research.
All of the conference’s sessions are now available on YouTube and the 2021 WiDS Conference Recap, including a talk titled “How Humans Build Models for the World” by Danielle Bassett, J. Peter Skirkanich Professor in Bioengineering and Electrical and Systems Engineering.
The Penn Bioengineering virtual seminar series continues on September 24th.
Speaker: Kevin Johnson, M.D., M.S.
Cornelius Vanderbilt Professor and Chair
Department of Biomedical Informatics
Vanderbilt University Medical Center
Date: Thursday, September 24, 2020
Time: 3:00-4:00 pm
Zoom – check email for link or contact firstname.lastname@example.org
Title: “Patients, Providers and Data: How the EMR and Data Science are Changing Clinical Care”
The electronic health record (EHR) is a powerful application of Systems Engineering to healthcare. It is a byproduct of a host of pressures including cost, consolidation of providers into networks, uniform drivers of quality, and the need for timely care across disparate socioeconomic and geographic landscapes within health systems. The EHR is also a fulcrum for innovation and one of the most tangible examples of how data science affects our health and health care. In this talk I will showcase projects from my lab that demonstrate the multi-disciplinary nature of biomedical informatics/data science research and translation using the EHR, and our current understanding of its potential from my perspective as a pediatrician, a researcher in biomedical informatics, a Chief Information Officer, an educator, and an advisor to local and international policy. I will describe advances in applying human factors engineering to support medical documentation and generic prescribing, approaches to improve medication safety, and innovations to support precision medicine and interoperability. I will present our efforts to integrate EHR-enabled data science into the Vanderbilt health system and provide a vision for what this could mean for our future.
Kevin B. Johnson, M.D., M.S. is Informatician-in-Chief, Cornelius Vanderbilt Professor and Chair of Biomedical Informatics, and Professor Pediatrics at Vanderbilt University Medical Center. He received his M.D. from Johns Hopkins Hospital in Baltimore and his M.S. in Medical Informatics from Stanford University. In 1992 he returned to Johns Hopkins where he served as a Pediatric Chief Resident. He was a member of the faculty in both Pediatrics and Biomedical Information Sciences at Johns Hopkins until 2002, when he was recruited to Vanderbilt University. He also is a Board-Certified Pediatrician.
Dr. Johnson is an internationally respected developer and evaluator of clinical information technology. His research interests have been related to developing and encouraging the adoption of clinical information systems to improve patient safety and compliance with practice guidelines; the uses of advanced computer technologies, including the Worldwide Web, personal digital assistants, and pen-based computers in medicine; and the development of computer-based documentation systems for the point of care. In the early phases of his career, he directed the development and evaluation of evidence-based pediatric care guidelines for the Johns Hopkins Hospital. He has been principal investigator on numerous grants and has been an invited speaker at most major medical informatics and pediatrics conferences. He also was the Chief Informatics Officer at Vanderbilt University Medical Center from 2015-2019.
See the full list of upcoming Penn Bioengineering fall seminars here.
One way to measure the success or influence of a researcher is to consider how many times they’re cited by other researchers. Every published paper requires a reference section listing relevant earlier papers, and the Web of Science Group keeps track of how many times different authors are cited over the course of a year.
In 2019, two members of the Penn Bioengineering department, Jason Burdick, Ph.D., and Danielle Bassett, Ph.D., were named Highly Cited Researchers, indicating that each of them placed within the top 1% of citations in their field based on the Web of Science’s index. For the past year, only 6,300 researchers were recognized with this honor, a number that makes up a mere 0.1% of researchers worldwide. Bassett’s lab looks at the use of knowledge, brain, and dynamic networks to understand bioengineering problems at a systems-level analysis, while Burdick’s lab focuses on advancements in tissue engineering through polymer design and development.
Burdick’s and Bassett’s naming to the list of Highly Cited Researchers demonstrates that their research had an outsized influence over current work in the field of bioengineering in the last year, and that new innovations continue to be developed from foundations these two Penn researchers created. To be included among such a small percentage of researchers worldwide indicates that Bassett and Burdick are sources of great impact and influence in bioengineering advancements today.
The developing human brain contains a cacophony of electrical and chemical signals from which emerge the powerful adult capacities for decision-making, strategizing, and critical thinking. These signals support the trafficking of information across brain regions, in patterns that share many similarities with traffic patterns in railway and airline transportation systems. Yet while air traffic is guided by airport control towers, and railway routes are guided by signal control rooms, it remains a mystery how the information traffic in the brain is guided and how that guidance changes as kids grow.
In part, this mystery has been complicated by the fact that, unlike transportation systems, the brain is not hooked up to external controllers. Control must happen internally. The problem becomes even more complicated when we think about the sheer number of routes that must exist in the brain to support the full range of human cognitive capabilities. Thus, the controllers would need to produce a large set of control signals or use different control strategies. Where internal controllers might be, how they produce large variations in routing, and whether those controllers and their function change with age are important open questions.
A recent paper published in Nature Communications – a product of collaboration among the Departments of Bioengineering and Electrical & Systems Engineering at the University of Pennsylvania and the Department of Psychiatry of Penn’s Perelman School of Medicine – offers some interesting answers. In their article, Danielle Bassett, Ph.D., Eduardo D. Glandt Faculty Fellow and Associate Professor in the Penn BE Department, Theodore D. Satterthwaite, M.D., Assistant Professor in the Penn Psychiatry Department, postdoctoral fellow Evelyn Tang, and their colleagues suggest that control in the human brain works in a similar way to control in man-made robotic and other mechanical systems. Specifically, controllers exist inside each human brain, each region of the brain can perform multiple types of control, and this control grows as children grow.
As part of this study, the authors applied network control theory — an emerging area of systems engineering – to explain how the pattern of connections (or network) between brain areas directly informs the brain’s control functions. For example, hubs of the brain’s information trafficking system (like Grand Central Station in New York City) show quite different capacities for and sensitivities to control than non-hubs (like Newton Station, Kansas). Applying these ideas to a large set of brain imaging data from 882 youths in the Philadelphia area between the ages of 8 and 22 years old, the authors found that the brain’s predicted capacity for control increases over development. Older youths have a greater predicted capacity to push their brains into nearby mental states, as well as into distant mental states, indicating a greater potential for diversity of mental operations than in younger youths.
The investigators then asked whether the principles of network control could explain the specific manner in which connections in the brain change as youths age. They used tools from evolutionary game theory – traditionally used to study Darwinian competition and evolving populations in biology – to ‘evolve’ brain networks in silico from their 8-year old state to their 22-year-old state. The results demonstrated that the optimization of network control is a principle that explains the observed changes in brain connectivity as youths develop over childhood and adolescence. “One of the observations that I think is particularly striking about this study,” Bassett says, “is that the principles of network controllability are sufficient to explain the observed evolution in development, suggesting that we have identified a quintessential rule of developmental rewiring.”
This research informs many possible future directions in scientific research. “Showing that network control properties evolve during adolescence also suggests that abnormalities of this developmental process could be related to cognitive deficits that are present in many neuropsychiatric disorders,” says Satterthwaite. The discovery that the brain optimizes certain network control functions over time could have important implications for better understanding of neuroplasticity, skill acquisition, and developmental psychopathology.