Stanford University
 
Laura D. Tyson

Laura D. Tyson

Digital Fellow

Influential scholar of economics and public policy; expert on trade and competitiveness

Laura D’Andrea Tyson is an influential scholar of economics and public policy and an expert on trade and competitiveness who has also served as a presidential adviser.

She is a distinguished professor of the Graduate School at the Haas School of Business, University of California, Berkeley. She also chairs the board of trustees at UC Berkeley’s Blum Center for Developing Economies, which aims to develop solutions to global poverty. She is the former faculty director of the Berkeley Haas Institute for Business and Social Impact, which she launched in 2013. She served as interim dean of the Haas School from July to December 2018, and served previously as dean from 1998 to 2001.

 
Marshall Van Alstyne

Marshall Van Alstyne

Digital Fellow

Marshall Van Alstyne is one of the leading experts in network business models.

He conducts research on information economics, covering such topics as communications markets, the economics of networks, intellectual property, social effects of technology, and productivity effects of information. As co-developer of the concept of “two-sided networks,” Marshall has been a major contributor to the theory of network effects, a set of ideas now taught worldwide. His co-authored article on the subject is a Harvard Business Review top 50 of all time.

Awards include two patents, National Science Foundation IOC, SGER, SBIR, iCorp and Career Awards, and eight best paper awards. His articles and commentary have appeared in Science, Nature, Management Science, Harvard Business Review, The New York Times, and The Wall Street Journal.

Affiliations

  • Boston University Questrom Professor in Management
  • Professor, Information Systems
 
Xiupeng Wang

Xiupeng Wang

Digital Fellow

Xiupeng Wang’s primary research interest is labor economics with a focus on the relationship between technology advances and  labor market dynamics.

His other interests include public policy, industrial organization, macroeconomics, and the economics of science and engineering. 

Prior to earning his PhD, Xiupeng earned a Master of Science in physics from New Jersey Institute of Technology.

 
Victor Yifan Ye

Victor Yifan Ye

Digital Fellow

Victor is a research scientist at Opendoor Technologies and a digital fellow at the Stanford Digital Economy Lab . His research covers topics in housing and urban economics, public finance, macro-fiscal policy, and the economics of AI, with the common denominator being the utilization of large-scale computable general equilibrium simulations.

Victor received his PhD in economics from Boston University, and an MS in statistical and economic modeling (MSEM) from Duke University, where he also received bachelors’ degrees in economics (B.S.) and philosophy (A.B.).

 
Irving Wladawsky-Berger

Irving Wladawsky-Berger

Digital Fellow

Dr. Irving Wladawsky-Berger is a research affiliate at MIT’s Sloan School of
Management and a fellow of MIT’s Initiative on the Digital Economy and MIT Connection Science.

He retired from IBM in May of 2007 after a 37-year career with the company, where his primary focus was on innovation and technical strategy. He led a number of IBM’s companywide initiatives including the Internet, Supercomputing, and Linux. He’s been Adviser on Digital Strategy and Innovation at Citigroup, at HBO, and at MasterCard; adjunct professor at the Imperial College Business School; and a guest columnist at the Wall Street Journal’s CIO Journal.

Dr. Wladawsky-Berger was co-chair of the President’s Information Technology Advisory Committee, and a founding member of the Computer Sciences and Telecommunications Board of the National Research Council. He is a fellow of the American Academy of Arts and Sciences. A native of Cuba, he was named the 2001 Hispanic Engineer of the Year. Dr. Wladawsky-Berger received an M.S. and a Ph. D. in physics from the University of Chicago.

Since 2005, Irving has been writing a weekly blog, irvingwb.com

 
Lynn Wu

Lynn Wu

Digital Fellow

Lynn Wu is an associate professor (with tenure) at the Wharton School. She teaches MBA, undergraduate and PhD classes about the use and impact of emerging technologies on business.

Her research examines how emerging information technologies, such as artificial intelligence and analytics, affect innovation, business strategy, and productivity. Specifically, her work follows three streams. In the first stream, she examines how data analytics and artificial intelligence affect firm innovation, business strategy, labor demand, and productivity for both large firms and startups. In her second stream, she studies how enterprise social media and online platforms affect work performance, career trajectories, entrepreneurship success, and the formation of new type of biases that arise from using technologies. In her third stream of research, Lynn leverages fine-grained nanodata available through online digital traces to predict economic indicators such as real estate trends, labor trends and product adoption.

Lynn has published articles in economics, management and computer science. Her work has been widely covered by media outlets, including, NPR, the Wall Street Journal, Businessweek, New York Times, Forbes, and The Economist. She has won numerous awards such as Early Career awards from INFORMS and AIS, best paper awards from Information System Research, AIS, ICIS, HICSS, CHITA, and Kauffman. She has also won the Dean’s teaching award.

Lynn received her undergraduate degrees from MIT (Finance and Computer Science), her master’s degree from MIT (Computer Science) and her Ph.D. from MIT Sloan School of Management (Management Science). Lynn has experiences working with a variety of firms in the technology industry (e.g. IBM, SAP, Google, Facebook etc), government agencies and think tanks (e.g the World Bank, the Russel Sage Foundation). She has also consulted and advised several startups. Prior to academia, she was a software engineer and a research scientist at MIT AI lab and IBM.

Stanford University