UVA Data Points

Interested in what a career in data science can look like? Here, we’re joined by two members of the School of Data Science Advisory Board: Heidi Lanford, co-founder of NavAlytix AI and former Chief Data Officer at Fitch Group, and Kane Geyer, Principal at PwC and most recently the leader of the U.S. and Global Chief Data Office. In conversation with Reggie Leonard from UVA’s School of Data Science, they share perspectives shaped by decades of experience leading data and AI initiatives across global organizations. Our Guests Heidi Lanford is an award-winning global executive with a track record of transformative leadership and operational expertise. She is the co-founder of NavAlytix AI, a technology startup that is focused on the adoption, impact and outcomes of AI. She was most recently the pioneering Chief Data Officer at Fitch Group (parent of Fitch Ratings), a Hearst Company. She joined Fitch from Red Hat (IBM), where she led their enterprise data, analytics and AI strategy. She has earlier executive leadership experience at Avaya, WPP and PwC, across the Americas, Asia, and Europe, in both B2B and B2C companies. Heidi is a frequent keynote speaker on AI strategy and transformation. She holds a BA in mathematics and statistics from the University of Virginia. She is a strategic advisor to Domino Data Labs and several other early-stage AI companies. She was previously an advisor to HearstLab, which provides investment and services to early-stage, women-led technology startups. Kane Geyer is a Principal at PwC where he has spent his career working with clients and internal stakeholders to transform businesses by integrating leading-edge decision-making capabilities and building high impact data and analytics teams. In his current role as leader of the U.S. and Global Chief Data Office, Kane oversees the evolution of the enterprise data and knowledge strategy to design and develop analytical capabilities for commercial and internal purposes. Serving in this capacity has been a phenomenal learning experience in leadership, collaboration, and navigating the complex risk and regulatory facets of delivering analytics capabilities at scale in a global marketplace. Prior to leading the Global and U.S. CDO, Kane served clients in PwC’s Consumer Markets vertical where he led multi-disciplinary teams across data, analytics, and technology competencies to deliver enterprise scale decision capabilities. Over a 20-year career, he built a fabric of experiences that invited him to see the world through business, technology, and operational eyes. Serving early in his career as analyst, engineer, and architect and later as strategist and operational leader yielded a sound professional foundation shaped by diverse perspectives and business challenges. The lessons learned over the course of a rewarding career have been many. Some were learned early and matured into core professional values and guiding principles. Others were harvested by taking calculated risks and learning through failure. The privilege of joining the School of Data Science Advisory Board presents a great opportunity to share some of those lessons and knowledge to help others navigate the path forward. Kane graduated from the University of Virginia in 1998 with a B.A. in Environmental Sciences. Following the ethos of living a lifetime of learning, he pursued graduate studies at the Leonard N. Stern School of Business, New York University where he earned an M.B.A. in 2010. Kane enjoys balancing his professional life and aspirations by maximizing his time outdoors and traveling. He currently resides in Connecticut with his wife and two children. Stay connected with UVA Data Points and UVA School of Data Science Catch all our latest episodes of UVA Data Points here:

Would you be able to recognize the subtle red flags that someone is being controlled, exploited, or groomed? In this conversation, we will dive into the complexities of understanding human trafficking and the role AI is playing to help law enforcement identify traffickers and their victims. Our guests are Kimberly Adams, who leads the strategic architecture of AINA Tech, and Shweta Jain, AINA’s Co-Founder and Technical Architect, whose background in digital forensics and cybersecurity shapes the system’s design. The conversation is led by Adam Tashman, Associate Professor of Data Science at UVA. Together, they discuss designing AI for defensibility, integrity, and institutional trust. Adam Tashman is an associate professor of data science, Director of the Data Science Capstone Program, and former Director of the Online M.S. in Data Science Program. Courses taught include reinforcement learning, distributed computing, programming for data science, mathematical finance, actuarial statistics, probability and statistics, and survival analysis. Research interests include AI in personalized medicine, digital health, computer vision, large language models, and quantitative finance. Kimberly Adams leads the strategic framing and execution architecture of AINA. Her work focuses on building AI systems that can withstand legal and institutional scrutiny, particularly in high-stakes environments such as human trafficking investigations. She has worked alongside DOJ-funded task forces and engaged with federal stakeholders to translate governance, procurement, and evidentiary requirements into system design constraints. Through programs such as NSF I-Corps and collaborations with academic partners, she structures how AINA retires institutional risk before deployment. Shweta Jain leads the technical architecture of AINA, focusing on defensibility, constrained inference, and system integrity. Her background in digital forensics and cybersecurity informs the development of AI systems designed to operate under evidentiary standards. She oversees the rigor, feasibility, and long-term survivability of AINA’s core architecture. She is Chair of the Department of Mathematics and Computer Science at John Jay College, an NSA-designated Center of Academic Excellence in Cyber Defense.

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.

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.

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.

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.

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?

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.

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

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.

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)

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.