Zhi Li

  • Assistant Professor
  • HYDROLOGY, WATER RESOURCES & ENVIRONMENTAL FLUID MECHANICS
Zhi Li in a button-down shirt with some trees in the background and a building behind the trees.

I study surface water across scales, both spatially (local, continental, and global) and temporally (hydrology, hydrometeorology, and hydroclimatology). My research focuses on flood prediction and monitoring by leveraging remote sensing platforms and hydrologic-hydraulic coupled models. The newly established Flood Lab will concentrate on four research themes: (1) high-resolution flood modeling and risk assessment, (2) extreme hydro-meteorological events under climate change, (3) AI4Science—including deep learning, large language models and intelligent agents, and (4) coupled analyses linking remote sensing, floods, public health and economics.

Recently, I have been investigating flood impacts on global health and rice yields as part of my postdoc position at the Stanford Doerr School of Sustainability. At INSTAAR, I plan to establish a research collaboratory to develop an integrated Flood-Agriculture-Climate-Economics-Disease (FACED) framework. This goal aligns with my career mission to address sustainability challenges in communities across multiple dimensions.

Education

  • PhD (Civil Engineering & Environmental Science): University of Oklahoma, 2022
  • MS (Hydraulic Engineering & Water Resources Management): National University of Singapore, 2019
  • BS (Hydraulic Engineering): Hohai University, 2017

Awards

  • Dean's Postdoc Fellow, Doerr School of Sustainability, Stanford University, 2023
  • Hoving Fellowship, University of Oklahoma, 2019

Research areas

  • Hydrologic science
  • Flood modeling
  • Artificial intelligence
  • AI for science