Ruyu Chen’s research interest lies at the intersection of economics of innovation, information systems, and business strategy. In her current research, she explores factors that influence technology adoption by firms, and how technology adoption influences follow-on innovations. She’s also interested in the power law distribution of wages within each occupation and how digitization might have affected it over time.
Before joining Stanford, Ruyu received her PhD in Managerial Economics from Cornell SC Johnson College of Business, and a graduate minor in Computer Science from Cornell University. She also holds a bachelor’s degree from Renmin University of China, and spent one exchange semester at the University of Copenhagen.
James is an MBA and MS Sustainability student at Stanford. Prior to joining the Lab, James co-founded Fingo – the first digital-only bank in Kenya, backed by Y Combinator. James started his career at McKinsey where he was an Engagement Manager focused on corporate business building and advanced analytics with McKinsey’s AI arm, Quantum Black.
James has been recognised as a Forbes 30 Under 30 and MIT Innovator Under 35. James studied Economics and Econometrics at the University of Warwick and the University of Hong Kong; he is particularly interested in understanding and measuring the economic potential of artificial intelligence in emerging markets.
José Ramón Enríquez is a postdoctoral fellow at the Stanford Digital Economy Lab (Stanford HAI) and the Golub Capital Social Impact Lab (Stanford GSB).
José Ramón obtained his Ph.D. in Political Economy and Government (PEG) from Harvard University in May 2023.
José Ramón studies the political economy of economic and political development with a focus on political accountability. Specifically, he has worked on understanding the role of information in improving political accountability, with a specific emphasis on misinformation, political polarization, and corruption; the causes and effects of criminal-political violence on democratic representation; and the effects of the lack of coordination across levels of government.
In his research, José Ramón relies significantly on quasi-experimental and experimental methods. He uses original fine-grained data, which he gathers and structures, originating from a variety of sources, such as administrative records, social media platforms, and online media. In some instances, he also uses formal analytic models to build theoretical frameworks and formulate original predictions to test empirically.
Before his doctoral studies, José Ramón obtained a B.A. in Economics and a B.A. in Political Science from Instituto Tecnológico Autónomo de México (ITAM) in Mexico City. He was raised in Durango, Mexico.
Ziv Epstein is a postdoctoral fellow at the Stanford Institute for Human-Centered AI. In his research, he seeks to bring a (more-than-)human-centered approach to the design of sociotechnical systems. In particular, he focuses on translating insights from design and the social sciences into the development of generative AI and social media platforms. In his dissertation, he explored ways to conceptualize and navigate attention online in order to develop interventions to mitigate the spread of misinformation and to promote collective intelligence: how do we move away from an attention economy, and towards an attention ecology?
Ziv has published papers in venues such as the general interest journals Nature, Science and PNAS, as well as top-tier computer science proceedings such as CHI and CSCW. His work has also received widespread media attention in outlets like the New York Times, Scientific American, and NPR.
Christina Langer’s research interests cover the fields of empirical labor economics and economics of education. Her research delves into the future of work, focusing on various aspects related to the supply and demand of skills and the evolving hiring practices of firms. She uses big, unstructured data like apprenticeship plan texts and online job postings, as well as administrative data, to estimate returns to skills and to investigate recent labor market trends like remote work or skills-based hiring.
J. Frank Li is an assistant professor at UBC Sauder School of Business, a digital fellow at Stanford University Institute for Human-Centered Artificial Intelligence Digital Economy Lab and a visiting fellow at NYU Stern Center for the Future of Management. His research stands at the nexus of the economics of information technology, focusing on AI and robots, technical skills and future of work, and organizational changes. He also studies how uncertainty shocks and competition affect firm strategic decisions such as investment, innovation, reorganization, and hiring.
Frank received his Ph.D. in business administration from Ross School of Business at the University of Michigan. He holds a BA in math and economics from the University of Michigan and an MA in economics from Duke University.
His current focus is developing new well-being metrics by using massive online choice experiments. He also studies the application of machine learning techniques to measure individual-level latent parameters. Lee
Before coming to Stanford, JJ worked at the MIT Initiative on the Digital Economy as a postdoctoral associate. He received his PhD in economics at Claremont Graduate University in 2019.
Lee has work experience as a business consultant, a financial analyst and a policy analyst in South Korea before his doctoral study. He also holds a bachelor degree in economics from Seoul National University and a master’s degree in public policy from KDI School of Public Policy and Management.
David’s research explores new and better ways to measure the modern and digital economy. He is particularly interested in advancing economic metrics and statistics on economic output and welfare.
Prior to joining the Stanford Digital Economy Lab, David worked as an economist at the OECD in Paris, and as a senior economist at the National Institute of Economic and Social Research (NIESR). As a research associate, he remains affiliated to the London-based Economic Statistics Centre of Excellence (ESCoE). David received his PhD from the London School of Economics.
Dan Sholler studies what happens when organizations and industries rapidly adopt new technologies. He primarily uses qualitative methods (interviewing, observation, surveys, and archival research) to understand why some workers resist new technologies; how management practices influence technology outcomes; and what role organizational and governmental policies play in shaping the decisions organizations and workers make about using new technologies.
Dan’s research aims to inform technology and labor management strategies, technology governance frameworks, and theories of technological change, especially change that happens in the workplace. He presents the results of the research in academic and practitioner-oriented outlets.
Dan is currently working as a project scientist in the Technology Management Program at the University of California, Santa Barbara College of Engineering. He works with Dr. Matt Beane and studies the implementation, management, and labor implications of robotics and automation in the manufacturing and logistics industries.
He is also the principal investigator on a project documenting the histories of two open-source software languages via oral histories and archival research, supported by the Sloan Foundation. He has also worked as a postdoc with the rOpenSci Project at UC Berkeley’s Institute for Data Science; completed the PhD program and did research at the University of Texas at Austin School of Information; and studied at the University of Pennsylvania’s Department of History and Sociology of Science.
Philip Trammell is an economics DPhil student at Oxford and research affiliate at GPI, an Oxford research institute. His research touches decision theory, game theory, and growth theory. He recently graduated from the MPhil with distinction, where he won the prize for best thesis. Philip also has undergraduate degrees in economics and mathematics from Brown, where he also won the prize for best econ thesis.
