Samuel N Araya

Postdoctoral Scholar

Stanford University

I am interested in data-driven analysis to address soil hydrology and biogeochemistry issues.

I have experience in laboratory-based soil science as well as computational work with machine learning, numerical simulations, and geospatial analyses.

My research experience includes studying the impact of wildfire on soil biogeochemistry, machine learning-based modeling of soil hydraulic conductivity at sample-scale, and field-scale investigations of soil moisture and biogeochemistry from unmanned aircraft systems and satellite-based remote sensing.


  • Soils
  • Data science
  • Machine learning
  • Spatial analysis


  • PhD in Environmental Systems, 2019

    University of California, Merced

  • MSc in Environmental Systems, 2014

    University of California, Merced

  • BSc in Land Resources and Environment, 2007

    Asmara University

Technical Skills

Soil Science

R | Python | JavaScript

Machine Learning




Linking sub-subsurface biogeochemistry with surface observations

Using data science methods to understand sub-surface biogeochemistry from surface observations

Rice arsenic contamination from a drone

Arsenic detection in rice from drone images using machine learning

Machine Learning Pedotransfer

Unsaturated hydraulic conductivity pedotransfer using machine learning.

Long-term conservation agriculture impact on soil hydrology

Impact of long-term conservation agriculture on soil hydraulic properties and moisture storage

Soil moisture observation from a drone

High resolution soil moisture prediction from drone images using machine learning


  • 367 Panama Street, Stanford, CA, 94305, United States
  • Green Earth Sciences, Room 323