Research

DeFi and FinTech

• The Paradox of Just-in-Time Liquidity in Decentralized Exchanges: More Providers Can Lead To Less Liquidity
  Agostino Capponi, Ruizhe Jia, and Brian Z. Zhu
  Working Paper
  Presented at: China International Conference in Finance 2024, Inter-Finance PhD Seminar, University of Michigan (Byrne Conference 2024), University
  of Chicago (Stevanovich Center Conference 2024), University of Toronto, The Latest in DeFi Research Conference 2024, Sydney Market Microstructure Conference 2023, INFORMS 2023

• Quantifying the Value of Revert Protection
  Brian Z. Zhu, Xin Wan, Ciamac C. Moallemi, Dan Robinson, and Brad Bachu
  Financial Cryptography and Data Security (FC 2025)
  Presented at: The Science of Blockchain Conference 2025, UC Santa Barbara (FBC Summit 2025), The Latest in DeFi Research Conference 2025, Financial Cryptography 2025

• What Drives Liquidity on Decentralized Exchanges? Evidence from the Uniswap Protocol
  Brian Z. Zhu, Dingyue Liu, Xin Wan, Gordon Liao, Ciamac C. Moallemi, and Brad Bachu
  Cryptoasset Analytics Workshop (CAAW 2025)
  Presented at: University of Chicago (Stevanovich Center Conference 2025), Cryptoasset Analytics Workshop 2025, University of Sydney

• Privacy-Enhanced Payment Systems
  Agostino Capponi, Michael J. Lee, and Brian Z. Zhu
  Working Paper
  Presented at: INFORMS 2025 (forthcoming), GSU-MS FinTech Conference 2025 (forthcoming), European Finance Association 2025, Bank of Canada (ICPSS 2025), Swiss National Bank (Cryptoasset and Financial Innovation Conference 2025), CREST Future of Money Workshop 2025

• Optimal Exiting for Liquidity Provision in Constant Function Market Makers
  Agostino Capponi and Brian Z. Zhu
  Working Paper
  Presented at: SIAM Conference on Financial Mathematics and Engineering 2025, Vienna Congress on Mathematical Finance 2025, Peter Carr Conference 2024, INFORMS 2024

• From Pools to Books: Modeling DeFi Liquidity in TradFi Terms
  Agostino Capponi and Brian Z. Zhu
  Manuscript available upon request
  Presented at: Brazilian Finance Meeting 2025 (as mini-course), Advanced Mathematical Methods for Finance 2025 (as mini-course), École Polytechnique, Bloomberg Quant Seminar

Machine Learning

• Unsupervised machine learning reveals slab hydration variations from deep earthquake distributions beneath the northwest Pacific
  Gilbert L. Mao, Thomas P. Ferrand, Jiaqi Li, Brian Z. Zhu, Ziyi Xi, Min Chen
  Communications Earth and Environment, Vol. 3, Art. 56 (2022)