Through the Lens: A Digital Depiction of Dyslexia

by Nathi Magubane

Artist-in-residence and visiting scholar Rebecca Kamen has blended AI and art to produce animated illustrations representing how a dyslexic brain interprets information.

A collage of artwork depicts a series of abstract visualizations of networks.
A work that Penn artist-in-residence Rebecca Kamen produced for the show, “Dyslexic Dictionary” at Arion Press in San Francisco. Here, she reinterprets Ph.D. candidate Dale Zhou’s network visualization. (Image: Cat Fennell)

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.

Undiagnosed dyslexia

“[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.”

Creativity and curiosity

This idea of curiosity and the patterns its neural representations could generate motivated “Reveal: The Art of Reimagining Scientific Discovery,” Kamen’s previous exhibit, which was inspired by the work of Penn professor Dani Bassett, assistant professor David Lydon-Staley and American University associate professor Perry Zurn on the psychological and historical-philosophical basis of curiosity.

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.”

Read the full story in Penn Today.

Rebecca Kamen is a visiting scholar and artist-in-residence in the Department of Physics & Astronomy in Penn’s School of Arts & Sciences.

Dale Zhou is a Ph.D. candidate in Penn’s Neuroscience Graduate Group.

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.

 

Dani Smith Bassett Receives 2022-23 Heilmeier Award

by Olivia J. McMahon

Dani Bassett, Ph.D.

Dani Smith Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering in Penn Engineering, has been named the recipient of the 2022-23 George H. Heilmeier Faculty Award for Excellence in Research for “groundbreaking contributions to modeling and control of brain networks in the contexts of learning, disease and aging.”

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.

Listen: ‘Curious Minds’ on NPR’s ‘Detroit Today’

by Ebonee Johnson

Twin siblings and scholars Dani S. Bassett of Penn and Perry Zurn of American University collaborated over half a dozen years to write “Curious Minds: The Power of Connection.” (Image: Tony and Tracy Wood Photography)

Twin academics Dani S. Basset, J. Peter Skirkanich Professor and director of the Complex Systems Lab, and Perry Zurn, a professor of philosophy at American University, were recently featured as guests on NPR radio show “Detroit Today” to discuss their new book, “Curious Mind: The Power of Connection.”

In their book, Basset and Zurn draw on their previous research, as well as an expansive network of ideas from philosophy, history, education and art to explore how and why people experience curiosity, as well as the different types it can take.

Basset, who holds 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, and Zurn spoke with “Detroit Today” producer Sam Corey about what types of things make people curious, and how to stimulate more curiosity in our everyday lives.

According to the twin experts, curiosity is not a standalone facet of one’s personality. Basset and Zurn’s work has shown that a person’s capacity for inquiry is very much tied to the overall state of their health.

“There’s a lot of scientific research focusing on intellectual humility and also openness to ideas,” says Bassett. “And there are really interesting relationships between someone’s openness to ideas, someone’s intellectual humility and their curiosity and also their wellbeing or flourishing,”

Listen to “What makes people curious and how to encourage the act” at “Detroit Today.”

Register for a book signing event for “Curious Minds: The Power of Connection,” on Friday, December 9th at the Penn Bookstore.

This story originally appeared in Penn Engineering Today.

Investing in Penn’s Data Science Ecosystem

by Erica K. Brockmeier

As part of a major University-wide investment in science, engineering, and medicine, the Innovation in Data Engineering and Science Initiative aims to help Penn become a leader in developing data-driven approaches that can transform scientific discovery, engineering research, and technological innovation.

From smartphones and fitness trackers to social media posts and COVID-19 cases, the past few years have seen an explosion in the amount and types of data that are generated daily. To help make sense of these large, complex datasets, the field of data science has grown, providing methodologies, tools, and perspectives across a wide range of academic disciplines.

But the challenges that lie ahead for data scientists and engineers, from developing algorithms that don’t exacerbate biases to ensuring privacy protections, are equally complex and, in some instances, require entirely new ways of thinking.

As part of its $750 million investment in science, engineering, and medicine, the University has committed to supporting the future needs of this field. To this end, the Innovation in Data Engineering and Science (IDEAS) initiative will help Penn become a leader in developing data-driven approaches that can transform scientific discovery, engineering research, and technological innovation.

“The IDEAS initiative is game-changing for our University,” says President Amy Gutmann. “This new investment allows us to boost our interdisciplinary efforts across campus, recruit phenomenal additional team members, and generate an even more sound foundation for discovery, experimentation, and design. This initiative is a clear statement that Penn is committed to taking data science head-on.”

Building on a foundation of existing expertise

Led by the School of Engineering and Applied Science, the IDEAS initiative builds upon the steadily gathering momentum of its data-centric research. The Warren Center for Network and Data Sciences has been a major catalyst for this type of work, generating foundational research on ethical algorithms and data privacy, as well as collaborations that have drawn in faculty from the Wharton School, Law School, Perelman School of Medicine, and beyond. In addition, Wharton’s Department of Statistics and Data Science is an active partner in research and teaching initiatives that apply statistical modeling across a wide variety of fields.

“One of the unique things about data science and data engineering is that it’s a very horizontal technology, one that is going to be impacting every department on campus,” says George Pappas, Electrical and Systems Engineering Department chair. “When you have a horizontal technology in a competitive area, we have to figure out specific areas where Penn can become a worldwide leader.”

To do this, IDEAS aims to recruit new faculty across three research areas: artificial intelligence (AI) to transform scientific discovery, trustworthy AI for autonomous systems, and understanding connections between the human brain and AI.

Penn already has a strong foundation in using AI for scientific discovery thanks in part to investments in basic research facilities such as the Singh Center for Nanotechnology and the Laboratory for Research on the Structure of Matter. Additionally, there are centers focused on connecting researchers from different fields to address complex scientific questions, including the Center for Soft and Living Matter, Center for Engineering Mechanobiology, and Penn Institute for Computational Science.

Developing “trustworthy” algorithms, ones that work reliably outside of situations in which they are trained, is another key component of the IDEAS initiative. Ongoing research at the Penn Research in Embedded Computing and Integrated Systems Engineering (PRECISE) Center, the General Robotics, Automation, Sensing & Perception (GRASP) Lab, and DARPA-funded projects on the safety of AI-based aircraft control provide a starting point for furthering Penn’s research portfolio on safe, explainable, and trustworthy autonomous systems.

In the area of neuroscience and how the human brain is similar to AI and machine learning approaches, research from PIK Professor Konrad Kording and Dani Bassett’s Complex Systems lab exemplifies the types of cross-disciplinary efforts that are essential for addressing complex questions. By recruiting additional faculty in this area, IDEAS will help Penn make strides in bio-inspired computing and in future life-changing discoveries that could address cognitive disorders and nervous system diseases.

Read the full story in Penn Today.

Penn Bioengineering Celebrates Five Researchers on Highly Cited Researchers 2021 List

The Department of Bioengineering is proud to announce that five of our faculty have been named on the annual Highly Cited Researchers™ 2021 list from Clarivate:

Dani Bassett, Ph.D.

Dani S. Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering
Bassett runs 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. They are a pioneer in the emerging field of network science which combines mathematics, physics, biology and systems engineering to better understand how the overall shape of connections between individual neurons influences cognitive traits.

Robert D. Bent Chair
Jason Burdick, Ph.D.

Jason A. Burdick, Robert D. Bent Professor in Bioengineering
Burdick runs the Polymeric Biomaterials Laboratory which develops polymer networks for fundamental and applied studies with biomedical applications with a specific emphasis on tissue regeneration and drug delivery. The specific targets of his research include: scaffolding for cartilage regeneration, controlling stem cell differentiation through material signals, electrospinning and 3D printing for scaffold fabrication, and injectable hydrogels for therapies after a heart attack.

César de la Fuente, Ph.D.

César de la Fuente, Presidential Assistant Professor in Bioengineering and Chemical & Biomedical Engineering in Penn Engineering and in Microbiology and Psychiatry in the Perelman School of Medicine
De la Fuente runs the Machine Biology Group which combines the power of machines and biology to prevent, detect, and treat infectious diseases. He pioneered the development of the first antibiotic designed by a computer with efficacy in animals, designed algorithms for antibiotic discovery, and invented rapid low-cost diagnostics for COVID-19 and other infections.

Carl June, M.D.

Carl H. June, Richard W. Vague Professor in Immunotherapy in the Perelman School of Medicine and member of the Bioengineering Graduate Group
June is the Director for the Center for Cellular Immunotherapies and the Parker Institute for Cancer Therapy and runs the June Lab which develops new forms of T cell based therapies. June’s pioneering research in gene therapy led to the FDA approval for CAR T therapy for treating acute lymphoblastic leukemia (ALL), one of the most common childhood cancers.

Vivek Shenoy, Ph.D.

Vivek Shenoy, Eduardo D. Glandt President’s Distinguished Professor in Bioengineering, Mechanical Engineering and Applied Mechanics (MEAM), and in Materials Science and Engineering (MSE)
Shenoy runs the Theoretical Mechanobiology and Materials Lab which develops theoretical concepts and numerical principles for understanding engineering and biological systems. His analytical methods and multiscale modeling techniques gain insight into a myriad of problems in materials science and biomechanics.

The highly anticipated annual list identifies researchers who demonstrated significant influence in their chosen field or fields through the publication of multiple highly cited papers during the last decade. Their names are drawn from the publications that rank in the top 1% by citations for field and publication year in the Web of Science™ citation index.

Bassett and Burdick were both on the Highly Cited Researchers list in 2019 and 2020.

The methodology that determines the “who’s who” of influential researchers draws on the data and analysis performed by bibliometric experts and data scientists at the Institute for Scientific Information™ at Clarivate. It also uses the tallies to identify the countries and research institutions where these scientific elite are based.

David Pendlebury, Senior Citation Analyst at the Institute for Scientific Information at Clarivate, said: “In the race for knowledge, it is human capital that is fundamental and this list identifies and celebrates exceptional individual researchers who are having a great impact on the research community as measured by the rate at which their work is being cited by others.”

The full 2021 Highly Cited Researchers list and executive summary can be found online here.

Dani Bassett Elected an American Physical Society Fellow

Dani Bassett, Ph.D.

Dani S. Bassett,  J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering, has been elected a 2021 Fellow of the American Physical Society (APS) “for significant contributions to the network modeling of the human brain, including dynamical changes caused by evolution, learning, aging, and disease.”

The prestigious APS Fellowship Program signifies recognition by one’s professional peers. Each year, no more than one half of one percent of the APS membership is recognized with this distinct honor. Bassett’s election and groundbreaking work in biological physics and network science will be recognized through presentation of a certificate at the APS March Meeting.

Bassett 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 recently collaborated with Penn artist-in-residence Rebecca Kamen and other scholars on an interdisciplinary art exhibit on the creative process in art and science at the Katzen Art Center at American University. They have also published research modeling different types of curiosity and exploring gender-based citation bias in neuroscience publishing.

“I’m thrilled and humbled to receive this honor from the American Physical Society,” says Bassett. “I am indebted to the many fantastic mentees, colleagues, and mentors that have made my time in science such an exciting adventure. Thank you.”

Read more stories about Bassett’s research here.

“This is What a Data Scientist Looks Like”

Speakers at the second annual Women in Data Science @ Penn Conference.

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.

Hosted by Penn Engineering, Analytics at WhartonWharton Customer Analytics and Wharton’s Statistics Department, the conference’s theme — “This is What a Data Scientist Looks Like” – emphasized the depth, breadth, and diversity of data science, both in terms of the subjects the field covers and the people who enter it.

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.

Read more about the conference at Wharton Stories: “How Women in Data Science Rise to the Top.

Originally posted in Penn Engineering Today.

Studying ‘Hunters and Busybodies,’ Penn and American University Researchers Measure Different Types of Curiosity

by Melissa Pappas

Knowledge networks were created as participants browsed Wikipedia, where pages became nodes and relatedness between pages became edges. Two diverging styles emerged — “the busybody” and “the hunter.” (Illustrations by Melissa Pappas)

Curiosity has been found to play a role in our learning and emotional well-being, but due to the open-ended nature of how curiosity is actually practiced, measuring it is challenging. Psychological studies have attempted to gauge participants’ curiosity through their engagement in specific activities, such as asking questions, playing trivia games, and gossiping. However, such methods focus on quantifying a person’s curiosity rather than understanding the different ways it can be expressed.

Efforts to better understand what curiosity actually looks like for different people have underappreciated roots in the field of philosophy. Varying styles have been described with loose archetypes, like “hunter” and “busybody” — evocative, but hard to objectively measure when it comes to studying how people collect new information.

A new study led by researchers at the University of Pennsylvania’s School of Engineering and Applied Science, the Annenberg School for Communication, and the Department of Philosophy and Religion at American University, uses Wikipedia browsing as a method for describing curiosity styles. Using a branch of mathematics known as graph theory, their analysis of curiosity opens doors for using it as a tool to improve learning and life satisfaction.

The interdisciplinary study, published in Nature Human Behavior, was undertaken by Danielle Bassett, J. Peter Skirkanich Professor in Penn Engineering’s Departments of Bioengineering and Electrical and Systems Engineering, David Lydon-Staley, then a post-doctoral fellow in her lab, now an assistant professor in the Annenberg School of Communication, two members of Bassett’s Complex Systems Lab, graduate student Dale Zhou and postdoctoral fellow Ann Sizemore Blevins, and Perry Zurn, assistant professor from American University’s Department of Philosophy.

“The reason this paper exists is because of the participation of many people from different fields,” says Lydon-Staley. “Perry has been researching curiosity in novel ways that show the spectrum of curious practice and Dani has been using networks to describe form and function in many different systems. My background in human behavior allowed me to design and conduct a study linking the styles of curiosity to a measurable activity: Wikipedia searches.”

Zurn’s research on how different people express curiosity provided a framework for the study.

Read the full story in Penn Engineering Today.

Danielle Bassett and Jason Burdick are Among World’s Most Highly Cited Researchers

Danielle Bassett and Jason Burdick
Danielle Bassett and Jason Burdick

The nature of scientific progress is often summarized by the Isaac Newton quotation, “If I have seen further it is by standing on the shoulders of giants.” Each new study draws on dozens of earlier ones, forming a chain of knowledge stretching back to Newton and the scientific giants his work referenced.

Scientific publishing and referencing has become more formal since Newton’s time, with databases of citations allowing for sophisticated quantitative analyses of that flow of information between researchers.

The Institute for Scientific Information and the Web of Science Group provide a yearly snapshot of this flow, publishing a list of the researchers who are in the top 1 percent of their respective fields when it comes to the number of times their work has been cited.

Danielle Bassett, J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering, and Jason Burdick, Robert D. Bent Professor in the department of Bioengineering, are among the 6,389 researchers named to the 2020 list.

Bassett is a pioneer in the field of network neuroscience, 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. Burdick is an expert in tissue engineering and the design of biomaterials for regenerative medicine; by precisely tailoring the microenvironment within these materials, they can influence stem cell differentiation or trigger the release of therapeutics.

Bassett and Burdick were named to the Web of Science’s 2019 Highly Cited Researchers list as well.

Originally posted in Penn Engineering Today.

Danielle Bassett on ‘A Radical New Model of the Brain’

In a ‘Wired’ feature, Bassett helps explain the growing field of network neuroscience and how the form and function of the brain are connected.

Danielle Bassett, Ph.D.

Early attempts to understand how the brain works included the pseudoscience of phrenology, which theorized that various mental functions could be determined through the shape of the skull. While those theories have long been debunked, modern neuroscience has shown a kernel of truth to them: those functions are highly localized to different regions of the brain.

Now, Danielle Bassett, Professor of J. Peter Skirkanich Professor of Bioengineering and Electrical and Systems Engineering, is pioneering a new subfield that goes even deeper into the connection between the brain’s form and function: network neuroscience.

In a recent feature article in Wired, Bassett explains the concepts behind this new subfield. While prior understanding has long relied on the idea that certain areas of the brain control certain functions, Bassett and other network neuroscientists are using advances in imaging and machine learning to reveal the role the connections between those areas play.

For Bassett, one of the first indicators that these connections mattered more than previously realized was the shape of the neurons themselves.

Speaking with Wired’s Grace Huckins, Bassett says:

“Neurons are not spherical — neurons have a cell body, and then they have this long tail that allows them to connect to many other cells. You can even look at the morphology of the neuron and say, ‘Oh, well, connectivity has to matter. Otherwise, it wouldn’t look like this.’”

Read more about Bassett and the field of network neuroscience in Wired.

Originally posted on the Penn Engineering blog.