Alia Braley is a PhD candidate in the Department of Political Science at UC Berkeley, and a project scientist at Stanford’ Digital Economy Lab. She was recently a visiting scholar at the SNF Agora Institute at Johns Hopkins University, the Director of Research and Education at the Albert Einstein Institution, a consultant at the World Bank Development Data Group, and a visiting researcher at the MIT Media Lab Human Dynamics Group.
She specializes in the study of democratic resilience in cases of political polarization and autocratic threat as well as civil resistance strategies in acute political conflict. The intervention featured in her recent publication, The Subversion Dilemma: Why Voters Who Cherish Democracy Participate in Democratic Backsliding, was the most effective at reducing polarization and strengthening democratic attitudes in Stanford University’s Strengthening Democracy Challenge mega-study.
She was previously a research assistant at the UC Berkeley Violence and Intervention Lab, at the United States Institute of Peace Nonviolent Action Program, and at the Harvard Kennedy School of Government Evidence for Policy Design Program.
She holds a Masters in Divinity from Harvard University, where her research focused on religion, ethics, and politics. During her time as a student, she served as an intern at the Center for Applied Nonviolent Action and Strategies in Belgrade, Serbia, and presented the findings of her master’s thesis on nonviolent action in Iraq and Syria at TEDx Salem.
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.
Basil Halperin is a postdoc at the Stanford Digital Economy Lab. In fall 2025, he will join the University of Virginia as an assistant professor of economics.
His research focuses on topics in monetary economics, macroeconomic growth, and AI.
Basil received my PhD in economics from MIT in 2024. He previously worked as a data scientist at Uber and as a quant at AQR Capital Management. He completed my undergrad at the University of Chicago.
Andreas Haupt is a postdoctoral fellow at Stanford’s Institute for Human-Centered AI. He completed his PhD in Engineering-Economic Systems at the CS and AI Laboratory and the College of Computing, MIT in fall 2024. He studies how the design of economic institutions that try to learn what participants want is affected by large-scale estimation.
Wang Jin is currently a research associate at the MIT Initiative on the Digital Economy and MIT Sloan School of Management. He was a former research fellow at IQSS Harvard University. Combining large-scale data from the Environmental Protection Agency and the Census,
Wang’s research concentrates on the impacts of information technology, structural management practices, and organizational structures on environmental performance and sustainability. He is also interested in identifying the effects of IT, management, and big data analytics on firms’ innovation capabilities.
Wang is currently involved in multiple Census projects, and has worked extensively within the U.S. Census Research Data Center, using business level confidential data protected under Title 13 and Title 26. He is also performing research on topics related to regulatory enforcement and firm compliance behavior.
Wang holds a Master’s degree in economics and recently received his PhD in economics from Clark University.
Sophia Kazinnik is a research scholar at the Stanford Digital Economy Lab, where she explores the intersection of artificial intelligence and economics. Prior to joining Stanford, Sophia worked as an economist and quantitative analyst at the Federal Reserve Bank of Richmond, where she was part of the Quantitative Supervision and Research group. While there, she contributed to supervisory projects targeting cyber and operational risks and developed NLP tools for supervisory purposes.
Broadly, her research focuses on applying Natural Language Processing (NLP) methods and Generative AI models to economic research, with particular emphasis on policy and central bank communication, financial stability, and cyber risk.
Sophia holds a bachelor’s degree in economics from Tel Aviv University in Israel and earned her doctoral degree in economics from the University of Houston.
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.
