Will Cong

Will Cong

  • Associate Professor of Finance
  • Department Editor, Management Science

Faculty Expertise

  • FinTech and AI
  • Corporate Finance
  • Entrepreneurship and Innovation
  • Applied Economic Theory
  • Investments
  • Digital Economics


Will Cong is the Rudd Family Professor of Management, professor of finance, and founding director of the FinTech Initiative at Cornell University. He is also a finance editor at the Management Science, faculty scientist at the Initiative for Cryptocurrencies & Contracts (IC3), research associate at the NBER, founder of multiple international research forums, a former Kauffman Junior Fellow, Poets&Quants World Best Business School Professor, and 2022 Top 10 Quant Professor. Cong was previously a faculty member at the University of Chicago after earning his PhD in finance and MS in statistics from Stanford University, and a master of arts in physics jointly with a bachelor's in math and physics from Harvard University.

Cong's research spans financial economics, information economics, fintech, digital economy, and entrepreneurship. He and his coauthors have pioneered the introduction of goal-oriented search and interpretable AI for finance, laid the foundations of tokenomics (covering categorization of tokens, cryptocurrency pricing, central bank digital currencies/payment systems, and optimal token monetary policy design), analyzed centralization issues and dynamic incentives in blockchains and DeFi, and developed data analytics for detecting market manipulation and better fintech regulation, among others.

Cong has won numerous best paper prizes and research grants and was invited to deliver keynote speeches at numerous international conferences and world-renowned institutions. Cong advises industrial leaders in fintech and quantitative investment, as well as various government and regulatory agencies.

Selected Publications

Recent Courses

  • NBAT 5900 - Advanced Topics in Finance
  • NBAE 5600 - Introduction to FinTech, Finnovation and Finalytics
  • BANA 5250 - Machine Learning for Investment

Academic Degrees

  • PhD Stanford University, 2014
  • MS Stanford University, 2013
  • MA Harvard University, 2009
  • BA Harvard University, 2009