Harvard Data Science Review Podcast

In this month’s episode of the Harvard Data Science Review Podcast, we explore the rapidly evolving concept of digital twins—dynamic, data-driven replicas of complex systems—and their growing influence across engineering, cities, healthcare, and society at large. Blending real-world case studies with big-picture insight, the discussion highlights how real-time data, sophisticated models, and massive computing power converge to let us safely test ideas, anticipate disruptions, and design smarter systems. Just as importantly, the episode tackles the critical questions of ethics, privacy, and public trust, making it an essential listen for anyone interested in where data science is headed—and how it can responsibly shape the world we live in. Our guests: Rachel Franklin is the executive director of the Center for Geographic Analysis at Harvard University  Patrick Johnson is the executive vice president of Corporate Research and Science at Dassault Systèmes

Fine wine meets data science in this month’s episode of the Harvard Data Science Review Podcast. Hosts Liberty Vittert Capito and Xiao-Li Meng explore how data, taste, and technology intertwine with Eric LeVine, founder of CellarTracker, the world’s largest community-driven wine database. What began as a personal project for managing a home cellar has evolved into a global platform with millions of users and billions of data points on wines, prices, and human preferences.  During the conversation, they unpack the origins of CellarTracker at Microsoft, how big data and machine learning reveal trends in taste and behavior, and the use of AI to predict “Will I like this wine?” They investigate how to find your digital wine twin, data quality and privacy, and how AI could change how we buy, drink, and enjoy wine without losing the human touch. Grab a glass and join us for a thoughtful conversation about curiosity, community, and enjoying life—responsibly. Our guest: Eric LeVine is president and CEO of CellarTracker, the world’s most comprehensive database. Previously he was a group program manager at Microsoft.

Artificial intelligence has made its way into the classroom—bringing excitement, confusion, and big questions about the future of learning. In this month’s episode of the Harvard Data Science Review Podcast, we explore how AI is transforming education with guests Chad Dorsey, president and CEO of the Concord Consortium, and Victor Lee, associate professor at the Stanford Graduate School of Education. Together, they discuss how teachers and students are using AI as a creative learning partner, the myths around AI-driven “cheating,” and how data literacy can empower the next generation. The conversation also dives into critical issues of equity, curiosity, and the evolving role of educators and parents in an AI-powered world—asking what it truly means to build a more human-centered future for learning. Tune in for an honest, hopeful look at the future of education and what it means to build a smarter, more human-centered classroom. Our guests: Chad Dorsey is president and CEO of the Concord Consortium, which has been an innovation leader in researching and developing STEM educational technology for the past 30 years.  Victor R. Lee is an associate professor in the Graduate School of Education at Stanford University and is faculty lead for the Stanford Accelerator for Learning's AI + Education program.

Will AI replace us, reshape our work, or create opportunities we’ve never imagined? For this month’s episode experts Ben Waber and Raffaella Sadun join the podcast to help us cut through the hype and discuss AI’s real impact on jobs, skills, and organizations. Drawing from research and industry experience, they tackle the myths of total automation, the need for firm-specific experimentation, and the evolving skills and management strategies required in the age of AI.  Join us as we take a pragmatic look at the challenges and opportunities as AI transforms how we work. Our guests:  Raffaella Sadun is the Charles E. Wilson Professor of Business Administration at Harvard Business School, and is a co-chair of Harvard Business School’s Project on Managing the Future of Work and co-PI of the Digital Reskilling Lab. Her research focuses on managerial and organizational drivers of productivity and growth in corporations and the public sector. Ben Waber is a leading thinker at the intersection of management, data, workplace, and people. He is currently a visiting scientist at MIT and a senior visiting scientist at Ritsumeikan University. Previously, he was the president and CEO of Humanyze, a workplace analytics company he co-founded.  

This month, we explore how data science and AI are transforming the wine industry—from vineyard planting and grape harvesting to customer engagement. Can advanced technologies help winemakers enhance quality, promote sustainability, and better match wines to consumers—all while preserving the essential human touch? Might these innovations be applied to other products as well? Join us as we discuss these questions and more with industry leaders Kia Behnia, CEO and co-founder of Scout, and Katerina Axelsson, CEO and founder of Tastry. Pour yourself a glass and tune in as we uncork the intersection of data, AI, and the art of winemaking. Our Guests: Kia Behnia is CEO and co-founder of Scout, an AI-powered analytics platform built for precision viticulture, and proprietor of Kiatra Vineyards and Neotempo Wines.  Katerina Axelsson is CEO and founder of Tastry, a sensory-sciences company that blends advanced analytical chemistry, machine learning, and AI to predict consumer preferences—especially in wine.