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:

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

This episode explores the intersection of neuroscience and data science with three experts in the field, Drs. John Darrell van Horn, Tanya Evans, and Teague Henry. As we know, the brain is complicated. People have been charting paths through the brain for decades, making breakthroughs and discoveries that have changed the world. In recent years though, new methodologies in brain research have made significant impacts. Advances in computing power, as well as techniques like machine learning, neural networks, and computer vision, have allowed researchers to ask questions and make discoveries that were not possible even ten years ago. Given these new approaches to studying the world’s most complicated organ, one could say that brain science is data science. Our guests make a compelling case.

This episode features a conversation between Lane Rasberry, Wikimedia-in-Residence at the University of Virginia School of Data Science, and Virginia Eubanks, author, journalist, and associate professor of political science at the University at Albany. 

The conversation was recorded in 2019 but the topics are still relevant today. Eubanks looks toward the future, warning of the unintended—or at times intended—consequences of emerging technologies. The discussion focuses on the effects of algorithmic automation, as well as the practice, policies, and implementation of these algorithms. Although she critiques the tech world, Eubanks also provides many reasons for optimism.

Virginia Eubanks authored the 2018 book Automating Inequality, which is a detailed investigation into data-based discrimination. She is also the author of Digital Dead End: Fighting for Social Justice in the Information Age and the co-editor, with Alethia Jones, of Ain’t Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith. She also writes for various outlets, including the Guardian, American Scientist, and the New York Times. Recently, Virginia began the PTSD Bookclub, an ongoing project that explores books about trauma and its aftermath. You can find this project and Virginia Eubank’s other projects at virginia-eubanks.com.

In this episode we’re bringing you a conversation on the future of academic data science recorded live at UVA Data Science’s Datapalooza 2022 event

Datapalooza is a flagship event for the School of Data Science. It’s typically held each year in November and features presentations by researchers here at UVA, as well as friends and collaborators of the School of Data Science.

In this episode we’re featuring a panel discussion between: 

Links:

Future of Academic Data Science video recording

Michigan Institue of Data Science 

UNC Charlottes School of Data Science

UVA School of Data Science