Overview
Prior to arriving at Duke, I was a postdoctoral research associate in the program in Atmospheric and Oceanic Sciences at Princeton University and had a dual appointment as a visiting research scientist at the NOAA Geophysical Fluid Dynamics Laboratory. I obtained my undergraduate degree at U.C. Berkeley where I received a Bachelor of Arts in Atmospheric Sciences and Applied Mathematics. For my graduate studies, I attended Princeton University where I completed a Ph.D. in Hydrology in the department of Civil and Environmental Engineering.
My research harnesses the existing petabytes of global environmental data to improve understanding of the terrestrial water cycle. More specifically, I focus on quantifying and uncovering the role of multi-scale spatial organization over land (i.e., heterogeneity) in the Earth system. To this end, my group's research has three overarching themes: 1) improve the representation of land heterogeneity in Earth system models, 2) harness environmental data to characterize the observed spatial patterns and features over land, and 3) quantify the sensitivity of the hydrologic cycle to spatial heterogeneity. The tools that my group uses include numerical modeling, satellite remote sensing, machine learning, and high performance computing.
I am currently looking for highly motivated Ph.D. and postdocs. If the research themes of my group are of interest to you, please don't hesitate to email me.
Current Duke Appointments & Affiliations
Recent Scholarly Works
High resolution modelling of temporal and spatial dynamics in soil conditions in subarctic Finland using HydroBlocks model
Journal article Hydrology and Earth System Sciences · August 11, 2026 The changing Arctic climate alters the dynamics of melting and freezing in the ground. A methodology has been developed to assess small magnitude, ice-induced earthquakes, called frost quakes, by estimating thermal stresses in the soil in Oulu, Fin ... Full text CiteEvaluating anisotropy-based Monin–Obukhov similarity theory over canopies and complex terrain
Journal article Quarterly Journal of the Royal Meteorological Society · July 1, 2026 Monin–Obukhov similarity theory (MOST) has long served as the basis for parameterizations of turbulence exchange between the surface and the atmospheric boundary layer in models for weather and climate prediction. Decades of research, however, have illumin ... Full text CiteImprovement of soil properties maps using an iterative residual correction method
Journal article Soil · May 19, 2026 Accurate mapping of soil properties is vital for many applications, yet existing models for digital soil maps often underestimate their spatial variability or prediction uncertainties, which introduces risk for applications such as irrigation and drainage ... Full text CiteRecent Grants
Observing and understanding the role of surface thermal heterogeneity in mesoscale circulations over AMF3 BNF: Implications for land-atmosphere interactions
ResearchPrincipal Investigator · Awarded by Department of Energy · 2024 - 2029Confronting the GFDL land model's sub-grid tiling scheme with observed space-time patterns of land surface temperature: Implications for hydrologic extremes
ResearchPrincipal Investigator · Awarded by National Oceanic and Atmospheric Administration · 2024 - 2027Artificial Intelligence for Enhancing Sustainability of Water, Nutrient, Salinity, and Pest Management in the Western USA
ResearchPrincipal Investigator · Awarded by University of California - Riverside · 2020 - 2026View All Grants