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UVA Data Points

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by UVA School of Data Science

5.0(9 reviews)
40 episodes
Updated Bi-weekly
Accepts GuestsHas SponsorsLocation 🇺🇸
52

Podcast Authority

Beta
FairBased on show quality, social media presence, reviews, charts, and more
Pod Engine
Quality57
Social0
YouTube86
Engagement32

Podcast Overview

a podcast exploring the world of data science

Language

🇺🇲

Publishing Since

8/24/2022

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52

Podcast Authority

Beta
FairBased on show quality, social media presence, reviews, charts, and more
Pod Engine
Quality57
Social0
YouTube86
Engagement32
7
Excellent Areas
3
Good Performance
9
Growth Opportunities
excellent
Episode Length
48 minutes
Performing excellently!
good
Show Notes Quality
3.0/5

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poor
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Every 33 days

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Recent Episodes

Episode thumbnail for Forging a Career in Data Science

May 13, 2026

Forging a Career in Data Science

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:

Episode thumbnail for Digital Twins

April 3, 2026

Digital Twins

In this episode of Data Points, we explore the rapidly evolving world of digital brain twins; personalized, data-driven models of the brain that could revolutionize medicine and neuroscience. Joining the conversation are two leading experts: Dr. Randy McIntosh, a pioneer in brain network analysis, and Dr. Emiliano Ricciardi, an expert in cognitive neuroscience and neuroimaging. Together, with Jack Van Horn, Professor with the School of Data Science and Department of Psychology, they'll dive into how these digital replicas of the brain could change the way we understand cognition, disease, and treatment.

Episode thumbnail for Defensibility in Human Trafficking

February 24, 2026

Defensibility in Human Trafficking

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.

40 total episodes available

Recent guests on UVA Data Points

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Arun Gupta

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Frequently asked questions

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What is UVA Data Points?

a podcast exploring the world of data science

How often does this podcast release new episodes?

This podcast updates bi-weekly.

Where can I listen to this podcast?

This podcast is available on 9 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.

Does this podcast accept guests?

Yes, this podcast regularly features guests.

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