UVA Data Points Castos https://uvadatapoints.castos.com a podcast exploring the world of data science Wed, 13 May 2026 11:36:56 +0000 en © 2022 US https://episodes.castos.com/63039339c8ad47-35894392/images/podcast/covers/c1a-o0g53-1xnrdoo1ugrw-dic8zd.jpg UVA Data Points https://uvadatapoints.castos.com a podcast exploring the world of data science UVA School of Data Science episodic a podcast exploring the world of data science UVA School of Data Science SDS_Comm@eservices.virginia.edu false https://feeds.castos.com/p4xr1 no <![CDATA[Forging a Career in Data Science]]> Wed, 13 May 2026 11:36:56 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2461651 https://uvadatapoints.castos.com/episodes/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:

Chapters

  • (00:00:43) - Meet the Board of the University of Virginia School of Data Science
  • (00:01:58) - What's Your Career Story on Your Resume
  • (00:03:13) - How to Get Out of Your Start Job
  • (00:05:50) - Getting Out of Data Science Boot Camp
  • (00:10:44) - Choosing the Right Path for Your Career
  • (00:14:38) - The Emergence of Data Science
  • (00:21:49) - Heidi on Quick Wins and Low-Hanging Fruit
  • (00:25:23) - How to Start a Business with Data and AI.
  • (00:29:35) - How Did You Build a Startup With No Full Time Employees?
  • (00:30:56) - Kane on Data Science and the Future
  • (00:33:05) - Bluefin Tuna
  • (00:33:24) - Quantum Intelligence: The Power of Data
  • (00:39:44) - The Future of Decision-Making Is AI
  • (00:42:16) - Citizen Data Scientists and Vibe Coding
  • (00:46:30) - What Advice Would You Have For Your Younger Self?
]]> false 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: https://uvadatapoints.castos.com

Want to learn more about the UVA School of Data Science: https://datascience.virginia.edu

]]> 00:54:28 <![CDATA[Digital Twins]]> Fri, 03 Apr 2026 20:26:13 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2413345 https://uvadatapoints.castos.com/episodes/digital-twins In this episode of UVA 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.

Chapters

  • (00:01:30) - Cognitive Science Podcast
  • (00:02:16) - What Exactly constitutes a Digital Brain Twin?
  • (00:13:12) - What are the computational requirements for a synthetic brain?
  • (00:16:53) - The computational requirements of the Digital Twin
  • (00:28:05) - Do Digital Twins Play a Role in Estimating Brain Age?
  • (00:34:09) - Ethical Implications of Digital Twins
  • (00:38:01) - Ethical Issues of the Digital Twin
  • (00:44:04) - Could a Digital Twin Brain Ever Become Conscious?
  • (00:51:30) - Digital Brain Twins: The Future of Science
  • (00:56:30) - Digital Brain Twins
]]> false In this episode of UVA 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.

]]> 00:58:23 <![CDATA[Defensibility in Human Trafficking]]> Tue, 24 Feb 2026 14:23:56 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2372706 https://uvadatapoints.castos.com/episodes/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.

]]> false 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.

]]> 00:33:49 <![CDATA[Data Protection in Humanitarian Action]]> Tue, 16 Dec 2025 17:14:10 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2291077 https://uvadatapoints.castos.com/episodes/data-protection-in-humanitarian-action In this episode, we explore data governance in the humanitarian sector. Our guests are Massimo Marelli, Head of the Data Protection Office at the International Committee of the Red Cross, and Ana Beduschi, a Professor of Law and Strategic Lead on the Fair and Inclusive Society at the Institute for Data Science and Artificial Intelligence (IDSAI) at the University of Exeter. The conversation is led by Aaron Martin Assistant Professor of Data Science here at UVA.

Together, they discuss topics from the book Data Protection in Humanitarian Action: Responding to Crises in a Data-Driven World. Of note, they share insights on how data regulation is shaping privacy and security for vulnerable communities and the role of international frameworks in addressing these challenges.

We're excited to welcome Margaux Jacks as the new host of our podcast. Margaux is the Creative Manager at the UVA School of Data Science, and producer of the podcast. She is thrilled to bring conversations about the world of data science to our listeners. We are incredibly grateful to Monica Manney for her wonderful work on the previous episodes.

Chapters

  • (00:00:03) - UVA Data Points: Data Governance in the humanitarian sector
  • (00:00:49) - The Impact of Data Protection in Humanitarian Action
  • (00:02:26) - The Digital Future of the Humanitarian Sector
  • (00:04:56) - Data Protection in the Humanitarian World
  • (00:09:54) - The role of data in the humanitarian sector
  • (00:12:57) - Immunity in the Data Protection Sphere
  • (00:16:07) - The Relationship between Data and Humanitarianism
  • (00:19:53) - Data Protection for the Humanitarian Sector
  • (00:24:59) - The Future of Data Protection in the humanitarian sector
  • (00:29:34) - Regional engagement in data protection law
  • (00:31:45) - Regional networks in the Digital world
  • (00:36:08) - The Future of Data Protection
  • (00:39:24) - On data protection in humanitarian programming
]]> false In this episode, we explore data governance in the humanitarian sector. Our guests are Massimo Marelli, Head of the Data Protection Office at the International Committee of the Red Cross, and Ana Beduschi, a Professor of Law and Strategic Lead on the Fair and Inclusive Society at the Institute for Data Science and Artificial Intelligence (IDSAI) at the University of Exeter. The conversation is led by Aaron Martin Assistant Professor of Data Science here at UVA.

Together, they discuss topics from the book Data Protection in Humanitarian Action: Responding to Crises in a Data-Driven World. Of note, they share insights on how data regulation is shaping privacy and security for vulnerable communities and the role of international frameworks in addressing these challenges.

We're excited to welcome Margaux Jacks as the new host of our podcast. Margaux is the Creative Manager at the UVA School of Data Science, and producer of the podcast. She is thrilled to bring conversations about the world of data science to our listeners. We are incredibly grateful to Monica Manney for her wonderful work on the previous episodes.

]]> 00:41:24 <![CDATA[Data Meets Art]]> Thu, 20 Nov 2025 14:22:19 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2234423 https://uvadatapoints.castos.com/episodes/artist-in-residency-nathalie-miebach 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
]]> false 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.

]]> 00:37:45 <![CDATA[Extreme Physics]]> Wed, 22 Oct 2025 13:57:46 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2169897 https://uvadatapoints.castos.com/episodes/extreme-physics 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.

]]> false 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.

]]> 00:31:28 <![CDATA[Trustworthy AI]]> Fri, 19 Sep 2025 18:25:13 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2145209 https://uvadatapoints.castos.com/episodes/trustworthy-ai 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.

]]> false 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.

]]> 00:26:42 <![CDATA[Brain Organoids: Unlocking Mysteries of Neuroscience]]> Mon, 18 Aug 2025 13:16:09 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2113924 https://uvadatapoints.castos.com/episodes/brain-organoids 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
]]> false 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.

]]> 00:48:33 <![CDATA[Venture Meets Mission: A Conversation with Arun Gupta]]> Tue, 17 Jun 2025 18:48:46 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2068167 https://uvadatapoints.castos.com/episodes/venture-meets-mission-a-conversation-with-arun-gupta 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.

]]> false 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.

]]> 00:57:03 <![CDATA[Women in Data Science, Charlottesville]]> Tue, 20 May 2025 21:04:09 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2043500 https://uvadatapoints.castos.com/episodes/women-in-data-science-charlottesville 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. 

]]> false 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. 

]]> 01:02:37 <![CDATA[Exploring the Protein Universe via AI]]> Wed, 23 Apr 2025 15:56:54 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/2018779 https://uvadatapoints.castos.com/episodes/exploring-the-protein-universe-via-ai 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.

]]> false 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.

]]> 00:30:58 <![CDATA[The Transformative Role of AI in the Credit Industry]]> Tue, 18 Mar 2025 18:35:51 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1995421 https://uvadatapoints.castos.com/episodes/data-insights 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. 

]]> false 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. 

]]> 00:42:24 <![CDATA[Surviving the Data Deluge]]> Thu, 20 Feb 2025 19:05:56 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1978149 https://uvadatapoints.castos.com/episodes/surviving-the-data-deluge 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?

]]> full false 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?

]]> 00:36:15 <![CDATA[Transforming Spotify Data Into Art]]> Tue, 21 Jan 2025 17:57:31 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1946802 https://uvadatapoints.castos.com/episodes/building-at-the-intersection-of-data-and-art 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.

]]> false 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.

]]> 00:43:29 <![CDATA[Misinformation and Image Manipulation in a Polarized America]]> Fri, 20 Dec 2024 20:14:56 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1924664 https://uvadatapoints.castos.com/episodes/misinformation-and-image-manipulation-in-a-polarized-america 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.

]]> full false 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.

]]> 00:46:25 <![CDATA[¡Viva la Ciencia de Datos en UVA!]]> Thu, 14 Nov 2024 13:55:52 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1889047 https://uvadatapoints.castos.com/episodes/viva-la-ciencia-de-datos-en-uva 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.

]]> false 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.

]]> 00:49:16 <![CDATA[Rebroadcast | Future Home of the UVA School of Data Science]]> Fri, 19 Apr 2024 17:01:27 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1724622 https://uvadatapoints.castos.com/episodes/rebroadcast-future-home-of-the-uva-school-of-data-science 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

]]> full 13 2 false 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

]]> 00:37:15 <![CDATA[The AI Playbook | A Conversation with Eric Siegel]]> Tue, 06 Feb 2024 17:25:00 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1655981 https://uvadatapoints.castos.com/episodes/the-ai-playbook-a-conversation-with-eric-siegel 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

]]> full 12 2 false 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

]]> 01:12:39 <![CDATA[The Future of Data Science Education | Live from Datapalooza]]> Mon, 08 Jan 2024 20:10:27 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1629294 https://uvadatapoints.castos.com/episodes/the-future-of-data-science-education-live-from-datapalooza 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.

]]> full 11 2 false 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.

]]> 01:01:50 <![CDATA[Rebroadcast | Advances in Sports Analytics]]> Thu, 21 Dec 2023 12:45:00 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1618351 https://uvadatapoints.castos.com/episodes/rebroadcast-advances-in-sports-analytics 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

]]> full 10 2 false 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

]]> 00:54:24 <![CDATA[The Future Impact of AI on Society Panel | Live from Datapalooza]]> Fri, 01 Dec 2023 13:00:00 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1606166 https://uvadatapoints.castos.com/episodes/the-future-impact-of-ai-on-society-panel-live-from-datapalooza 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)
]]> full 9 2 false 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)
]]> 00:58:09 <![CDATA[A View From Space | How LiDAR and Hyperspectral Imaging are Changing Science]]> Thu, 02 Nov 2023 18:00:00 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1588453 https://uvadatapoints.castos.com/episodes/a-view-from-space-how-lidar-and-hyperspectral-imaging-are-changing-science 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.

]]> full 8 2 false 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.

]]> 00:41:27 <![CDATA[Swimming with Data | Diving into Student Life]]> Tue, 03 Oct 2023 16:00:00 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1567152 https://uvadatapoints.castos.com/episodes/swimming-in-data-a-conversation-with-uva-student-athletes 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.

]]> full 7 2 false 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.

]]> 00:47:20 <![CDATA[Perspectives on the Meeting of Wikipedia & Artificial Intelligence]]> Tue, 22 Aug 2023 11:00:00 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1539719 https://uvadatapoints.castos.com/episodes/artificial-intelligence-wikipedia Excavating the Mother Lode of Human-Generated Text: A Systematic Review of Research That Uses the Wikipedia Corpus

]]> full 6 2 false Excavating the Mother Lode of Human-Generated Text: A Systematic Review of Research That Uses the Wikipedia Corpus

]]> 01:15:50 <![CDATA[A.I. Goes to School: The Future of Artificial Intelligence in Higher Ed]]> Tue, 20 Jun 2023 11:05:00 +0000 UVA School of Data Science https://permalink.castos.com/podcast/44037/episode/1496607 https://uvadatapoints.castos.com/episodes/ai-goes-to-school-the-future-of-artificial-intelligence-in-higher-ed

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.

]]> full 5 2 false

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.

]]> 00:40:49