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.

To view the full digital exhibition visit: https://story.datascience.virginia.edu/ The Story of Us is a digital brand showcase that chronicles the creation of a data science school at the University of Virginia. From an idea to an institute, and now to the first school of its kind in the nation, this bespoke, interactive website tells the story through written and spoken narrative supported by multimedia, archival documentation, and testimony from a diversity of voices. The result is a unique brand piece that combines technology with art, a retrospective of one school’s past and how it will inform its future. It was commissioned by the School of Data Science to mark the opening of its new building in April 2024. The Story of Us website was built by John Baxton, senior web developer for the School of Data Science, who worked in close collaboration with Sue Haas, the School’s information technology director. The designs for the site were created by the Charlottesville-based Journey Group. Video interviews and the audio version of The Story of Us were recorded and edited by Cody Huff, multimedia producer for the School of Data Science, who also coordinated the curation of assets for the project. Monica Manney provided the narration. Research and editorial content for the project were provided by the School of Data Science communications team of Huff, Cooper Allen, Alyssa Brown, Emma Candelier, and Kirsten Samuels. The Story of Us would not have been possible without the cooperation and generous time provided by the key figures interviewed for this project. They are Cathy Anderson, Phil Bourne, Don Brown, Arlyn Burgess, Rick Horwitz, Reggie Leonard, Melissa Phillips, Jim Ryan, Teresa Sullivan, and Jaffray Woodriff. And to all the students, faculty, and staff who contributed to this story over the years, the School of Data Science will forever be grateful.

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.comhttps://www.darden.virginia.edu/faculty-research/centers-initiatives/data-analytics/bodily-professorhttps://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.

Excavating the Mother Lode of Human-Generated Text: A Systematic Review of Research That Uses the Wikipedia Corpus

In this episode we’re looking at the past, present, and future of artificial intelligence in higher education. To explore this topics we’re featuring a conversation between Phil Bourne, the dean of the UVA School of Data Science, and Jeffrey Blume, the Associate Dean for Academic and Faculty Affairs, also at UVA Data Science. Jeffrey and Phil discuss the recent trends in artificial intelligence and they look at how this will impact the student experience, the faculty and staff experience, and the research landscape in higher education.

This episode was recorded during the Miller Center’s 2023 William and Carol Stevenson Conference, U.S. China Tech Competiton: Has Democracy Met its Match?  For more info on this conference, as well as to watch the video versions, follow this link: https://millercenter.org/news-events/events/us-china-tech-competition-has-democracy-met-its-match This episode features the first panel discussion from the conference entitled: Apps, platforms, and surveillance  How might apps and other technology platforms play a role in Chinese government data-gathering efforts? What are potential policy responses to the increasingly complex data flows between the United States and China? This panel addresses the long-term stability of U.S. technology infrastructure and related concerns for U.S. national security.  Josh Chin, Kara Frederick, Shanthi Kalathil, Aynne Kokas (moderator)

In this episode, we're thrilled to have Dr. Aynne Kokas, a C.K. Yen Professor at the Miller Center and an associate professor of media studies at the University of Virginia. Kokas’ research examines Sino-U.S. media and technology relations. Dr. Kokas is also the author of the critically acclaimed book "Trafficking Data: How China Is Winning the Battle for Digital Sovereignty," which we will be referring to frequently throughout this conversation. We will also touch on a few topics that were discussed in her recent conference at the Miller Center titled "U.S.-China Tech Competition: Has Democracy Met Its Match?" During the event, Dr. Kokas and other experts discussed a variety of issues related to the ongoing tech competition between the US and China. For example, they explored the ways in which apps and other technology platforms may be used by the Chinese government for data-gathering purposes, and examined potential policy responses to the increasingly complex data flows between the two countries. Additionally, they discussed the long-term stability of US technology infrastructure and its implications for national security. In addition, there were panels that discussed the digital economy, climate, tech infrastructure, and political influence between China and the US. In this episode we'll be discussing data policy for US-China technology, a topic that has become increasingly relevant in recent years as the two countries continue to compete for dominance in the tech industry. We'll delve into the differences in approach to data policy between China and the United States, the implications of these differences, and how China's digital silk road initiative is expanding its influence over the global digital economy. We'll also discuss the challenges of balancing economic benefits against concerns about national security and human rights, and the future of the technology industry in light of these trends. Links: U.S.–China tech competition: Has democracy met its match? Aynne Kokas website: https://www.aynnekokas.com/ Trafficking Data: How China Is Winning the Battle for Digital Sovereignty