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 Appointments & Affiliations
Recent Publications
HydroBlocks-MSSUBv0.1: a multiscale approach for simulating lateral subsurface flow dynamics in Land Surface Models
Journal Article Geoscientific Model Development · January 15, 2026 Groundwater is critical in the hydrological cycle, impacting water supply, agriculture, and climate regulation. However, current Land Surface Models (LSMs) often struggle to accurately represent the multiple spatial scales of subsurface flow primarily due ... Full text CiteImprovement of Soil Properties Maps using an Iterative Residual Correction Method
Preprint · November 21, 2025 Full text CiteCatchment Attributes and MEteorology for Large-Sample SPATially distributed analysis (CAMELS-SPAT): Streamflow observations, forcing data and geospatial data for hydrologic studies across North America
Journal Article Hydrology and Earth System Sciences · October 28, 2025 We build on the existing Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) dataset to present a new dataset aimed at hydrologic studies across North America, with a particular focus on facilitating spatially distributed studies. The da ... 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