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Here we explore the intersections of data, art, and storytelling. Our guest, Nathalie Miebach, is an internationally-recognized data artist and the School of Data Science’s inaugural Artist-in-Residence.

Using materials like reed and paper, she transforms complex datasets into woven sculptures and musical scores, inviting us to view and even hear data in new ways. Joining her is Alex Gates, assistant professor of data science at the University of Virginia research examines how patterns of connection shape creativity, innovation, and discovery.

Together, they discuss what happens when data meets art.

Chapters (00:00:01) - Data Points: When Art Meets Science(00:00:46) - Ian and Nicole: Introduction(00:06:18) - How Stories Get Made(00:09:59) - Basket Weaving Visualizing Data(00:20:33) - Wonders of the World(00:25:47) - Data and Artist Residency(00:27:50) - Breaking Habits in Creativity(00:30:06) - What is Data Science: Craftsmanship?(00:34:50) - How Art Affects Our Understanding of Data

In this episode, we explore how data science is helping researchers simulate and understand some of the most extreme physical events on Earth, from floods in Texas to hypersonic flight. Our guests are Stephen Baek, a leading expert in geometric deep learning and associate professor of data science at the University of Virginia, and Jack Beerman, a Ph.D. student whose work is already shaping real-world applications.

Together, they discuss how AI is transforming fields like weather forecasting, materials design, sports performance, and military innovation—and why graduate researchers like Jack are essential to moving this work forward.

Here we dive into one of the most timely and important topics in tech: Trustworthy AI. What does it really mean for artificial intelligence to be “trustworthy”? And why should it matter to you?

To help us unpack these questions, we’re joined by Farhana Faruqe, a data scientist, researcher, and entrepreneur, specializing in research related to Trustworthy AI, and Dr. Larry Medsker, a leading expert in AI ethics and policy. With experience in neural networks, AI systems, and policy-making, the two bring a wealth of insight into how we can, and must, develop artificial intelligence that is safe, ethical, and accountable.

In this episode, we’re diving into a fascinating intersection of cutting-edge science and data innovation. As technology continues to evolve, researchers are increasingly turning to brain organoids, (miniature, lab-grown models of the human brain) to unravel some of the most complex mysteries of neuroscience. We’re joined by three brain organoid experts: Thomas Hartung, Professor of Environmental Health and Engineering at Johns Hopkins University; Jack Van Horn, Professor of Data Science and Psychology at the University of Virginia;  and Lulu Jiang, Assistant Professor of Neuroscience, also at the University of Virginia. Together, they’ll shed light on how brain organoid technology is reshaping our understanding of the brain, and how data science is playing a crucial role in unlocking its secrets.

Chapters (00:00:51) - Brain Organizations(00:05:54) - Brain Organoids for drug discovery and immunology(00:13:53) - Alzheimer's disease in the organoid system(00:15:49) - What are the standards in the field of brain organoids?(00:22:44) - Big Data and Intelligence in the Brain(00:26:50) - Alzheimer's disease, the human brain(00:30:39) - The computational twin of the brain(00:37:23) - The quest for precision medicine in the brain(00:42:17) - The human brain in an organoid(00:43:21) - Will Brain Derived Organoids Replace Animal Models in Neurodegener

Explore how entrepreneurship and innovation can intersect with public service to drive meaningful impact. Join Dean Philip Bourne and the UVA School of Data Science community for an inspiring conversation with Arun Gupta, CEO of the NobleReach Foundation and author of Venture Meets Mission. 

Drawing from his extensive experience, Gupta will share insights on creating ventures with a mission-driven focus, discuss trends shaping the future of public service innovation, and offer practical advice for students aspiring to make a difference in this space. Whether you're passionate about social impact, curious about launching your own venture, or exploring career paths that combine innovation and public good, this conversation is not to be missed.

In this episode, we welcome you to the 2025 Women in Data Science Charlottesville event hosted at the University of Virginia School of Data Science. WiDS Charlottesville seeks to increase the participation of women in data science and feature outstanding women doing outstanding work.

Leading the conversation is Lisa Bowers, a former executive with Genentech/Roche and current director of UVA’s Enterprise Studio. She is joined by our keynote speaker Lexi Reese, CEO and Co-Founder of Lanai Software and UVA alumna, who brings experience spanning tech giants like Google and Gusto. Drawing from their wealth of knowledge at the intersection of innovation and enterprise, Reese and Bowers share their unique perspectives on how data science is shaping the future of work and innovation.

From empowering the next generation of data scientists to the real-world impact of AI, this fireside chat dives deep into what it means to build meaningful, transformative careers in data science. 

Here we explore how data science is revolutionizing our understanding of protein structures, with a special focus on the exciting developments in protein folding and evolution. We’re joined by two experts in the field: Philip Bourne, the founding dean of the UVA School of Data Science, and Cam Mura, a biomolecular data scientist. From new tools like DeepUrfold to the future of biomedical applications, Bourne and Mura provide a unique look into how cutting-edge technology is transforming the world of molecular biology.

UVA School of Data Science graduates pursue many career paths, including government, health care, technology, retail, and... finance. In this episode, we hear from two UVA data science alumni who put their data science degrees to work every day in their roles at Octus, a financial services company that uses data to provide insights to its clients in banking and legal services.

They discuss the integration of AI into various industries, the challenges of information overload, and the role of human expertise.We welcome Charu Rawat and Yihnew Eshetu, who earned their M.S. in Data Science degrees from UVA in 2019 and 2021, respectively, and Ben Rogers, vice president of AI and advanced analytics at Permira. 

One of the most pressing challenges in our increasingly data-driven world is the Data Deluge—the overwhelming flood of information that we generate and record every single day. With us are three experts from the University of Virginia’s School of Data Science. Phil Bourne, a professor of biomedical engineering and the founding dean of the school of data science, is joined by Terence Johnson and Alex Gates, both assistant professors of data science. Together, they have been exploring innovative methods to make sense of the vast oceans of data we’re all swimming in.

This episode unpacks the challenges of the data deluge—what it means for businesses, researchers, and society at large—and explore the strategies we can use to navigate it. How do we make sense of so much information? How do we ensure the ethical use of this data? And what opportunities does this overwhelming flood of data open up for the future?

Many of us look forward to our Spotify wrapped at the end of the year. It's fun to see your whole year in music reflected back to you in the form of auras and moods and, of course, ranked lists, all powered by the cold, hard data of our listening habits. But there's so much more data available to visualize as art. That's what our guest, Pete Cybriwsky does. Pete is an entrepreneur and an award winning artist building at the intersection of data and art. In this podcast, you'll hear him in conversation with Lane Rasberry wikimedian in residence at the UVA School of data science. 

If you want to learn more about Pete's work, check out his new app Day By Data.

To turn your spotify data into art, visit ngenart.com.

In recent elections, the rise of misleading content—ranging from manipulated images to false narratives—has sparked growing concerns about misinformation and disinformation. How does this wave of deceptive content deepen political divides, shape voter perceptions, and erode trust? And what does it mean for our access to reliable information? Last month, the UVA Karsh Institute of Democracy and the School of Data Science co-hosted an in-depth discussion to ask these pressing questions and uncover the challenges at the intersection of truth, trust, and democracy.

Guests included Mona Kasra, associate professor of digital media design at the University of Virginia; Francesca Tripodi, associate professor at the University of North Carolina Chapel Hill and David Nemer, assistant professor in media studies at the University of Virginia.

If you would like to learn more about the Karsh Institute of Democracy or the School of Data Science, please visit karshinstitute.virginia.edu or datascience.virginia.edu.

Data science is an incredibly diverse and global field of study and practice. In order to tackle some of our most challenging issues ranging from climate change to cognition, we need data and data scientists from all over the world to make advances in research, technology and innovation. To talk about their research interests and the importance of having diverse, global perspectives in the field of data science, this episode of UVA Data Points features a conversation by Javier Rasero, Assistant Professor of Data Science, and two University of Virginia data science students: Marco Gutiérrez Chavezis a first-year Ph.D. student from Peru and Mercedes Mora-Figueroa de Liñán is an M.S. in Data Science student from Spain.

The UVA School of Data Science was formed in September 2019 and has since grown in its collaborations, partnerships, program offerings, and teaching and research personnel. We are now constructing a new facility that will house the School of Data Science at the University of Virginia.

The new building is in the first phase of development and, once complete, will link the University's Central Grounds with the athletic fields and North Grounds. The 60,000-square-foot building is the future home of the UVA School of Data Science and will serve as the gateway to the new Emmet-Ivy Corridor and the Discovery Nexus.

This bonus episode is a conversation between UVA architect Alice Raucher and Mike Taylor, a principal with Hopkins Architects. Both Alice and Mike have been instrumental in the building’s design. Alice has also played a key role in the development of the Ivy Corridor. Mike and Alice take a deep dive into the thought process behind the building’s design, its relationship to the University and its history, the land's unique topography, and its significance to future projects along the Ivy Corridor. 

Links:

Hopkins Architects

School of Data Science New Building Website

In his new book, The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, Eric Siegel offers a detailed playbook for how business professionals can launch machine learning projects, providing both success stories where private industry got it right as well as cautionary tales others can learn from.

Siegel laid out the key findings of his book in our latest episode during a wide-ranging conversation with Marc Ruggiano, director of the University of Virginia’s Collaboratory for Applied Data Science in Business, and Michael Albert, an assistant professor of business administration at UVA's Darden School. The discussion, featuring three experts in business analytics, takes an in-depth look at the intersection of artificial intelligence, machine learning, business, and leadership.

http://www.bizML.com

https://www.darden.virginia.edu/faculty-research/centers-initiatives/data-analytics/bodily-professor

https://pubsonline.informs.org/do/10.1287/LYTX.2023.03.10/full/

https://www.kdnuggets.com/survey-machine-learning-projects-still-routinely-fail-to-deploy

CRISPDM: https://en.wikipedia.org/wiki/Cross-industry_standard_process_for_data_mining

CRM: https://en.wikipedia.org/wiki/Customer_relationship_management

This panel delves into how the faculty at UVA's School of Data Science are actively working to craft a liberal arts curriculum suitable for the digital age, one that not only adapts to but embraces changes in technology and practice. The panel discusses the future of data science education, including in K-12, the school’s guiding philosophy for its undergraduate and graduate programs (minor, B.S., online and residential M.S., Ph.D.), and the merits as well as challenges that arise when constructing a new educational curriculum for a new discipline.

Because of advances in machine learning, wearable technology, and computer vision, the field of sport analytics is a whole new game. This episode gets into the details on what is new, the impact of analytics and technology on athletes and sports, as well as the ethics surrounding its implementation. Three experts from the University of Virginia School of Data Science met to discuss this exciting topic: Natalie Kupperman, Stephen Baek, and Don Brown.  

On behalf of everyone here at the School of Data Science, thank you and we’ll see you next year

Artificial intelligence has the potential to change our societies, economies, and political systems in both intentional and unintended ways. While it is difficult to understand the full extent of what the long-term impacts may be, we have enough shared knowledge and expertise to predict the likely shapes that these changes may take—both for better and for worse. More importantly, we should ask ourselves what kind of future we want AI to help us create: what we want from the future of AI should ultimately determine the future of AI. This panel will bring together experts to discuss the intersection of AI and society and offer suggestions for how AI might work within a just, inclusive, sustainable, and fair digital future. 

Panelist

Farhana Faruqe, Assistant Professor of Data Science Sarah Lebovitz, Assistant Professor of Commerce Larry Medsker, Research Professor, George Washington University  Mar Hicks, Associate Professor of Data Science (moderator)

The latest episode of UVA Data Points features Don Brown, the senior associate dean for research at the School of Data Science, and professor Bill Basener as they discuss remote sensing, which is the process of collecting data about an object without contacting it.

The discussion traces the history of remote sensing, its many applications, and the challenges involved in gathering accurate information. The two take an in-depth look at Basener’s research, including his work with LiDAR and hyperspectral imaging.  Basener also explains the one aspect of this burgeoning technology that keeps him up at night.

This episode is a collaboration between UVA Data Points and Hoos in STEM.

This episode of UVA Data Points features Ken Ono discussing the growth of data science at UVA and its increasing importance in various disciplines, including how he uses it to help swimmers improve performance. Ono is a professor of mathematics and STEM advisor to the provost, as well as a professor of data science by courtesy. He recently supported the women's team at the U.S. Olympic Trials in Japan.

Ono speaks with three UVA swimmers who are pursuing graduate degrees in data science and statistics while also performing as student-athletes: August Lamb, Kate Douglass, and Will Tenpas. They discuss student life, balancing academics with swimming, and how data science and mathematics are helping them win championships.