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Samuel N Araya

Data Scientist

Hello, and welcome to my website!

I’m passionate about leveraging data science, machine learning, and geospatial analysis to unlock insights within the environment, agriculture, and other data-rich domains. This passion has driven my journey in tackling complex soil and environmental challenges through a blend of traditional research and cutting-edge innovation, from hands-on field and lab work to harnessing the power of machine learning and drone technology.

I earned my Ph.D. and M.S. in Environmental Science from UC Merced, specializing in soil physics and soil biogeochemistry, with a strong focus on data-driven approaches. I further honed my expertise through post-doctoral research in soil science at Stanford.

Today, I leverage my skills as a Data Scientist at Corteva Agriscience, contributing to boosting agricultural productivity and sustainability. My work revolves around using data to inform critical decisions and develop innovative solutions for the future of agriculture.

If you share my fascination with the potential of data to unlock solutions for a healthier planet, let’s connect and explore the possibilities together. You can find my detailed experiences in my resume and CV.

Interests

  • Soils
  • Data science
  • Machine learning
  • Spatial analysis

Education

  • PhD in Environmental Systems (Soil Physics), 2019

    University of California, Merced

  • MSc in Environmental Systems (Soil Biogeochemistry), 2014

    University of California, Merced

  • BSc in Land Resources and Environment, 2006

    Asmara University

Skills

Programming Languages

Python, R, JavaScript, SQL

Geospatial Analysis

Google Earth Engine, ArcGIS, QGIS

Version Control & DevOps

Git, CI/CD Pipelines, Docker

Machine Learning & AI

Regression, Classification, Clustering, Dimensionality Reduction

Data Visualization

Matplotlib, Seaborn, ggplot2

Publications

Samuel N Araya, Mitchell, J. P., Hopmans, J. W., Ghezzehei, T. A. (2022). Long-term impact of cover crop and reduced disturbance tillage on soil pore size distribution and soil water storage. SOIL.

DOI

Mitchell, J. P., Shrestha, A., Epstein, L., Dahlberg, J. A., Ghezzehei, T. A., Samuel N Araya, Richter, B., Kaur S., Henry, P., Munk, D. S., Light, S., Bottens, M., Zaccaria, D. (2022). No-Tillage Sorghum and Garbanzo Yields Match or Exceed Standard Tillage Yields. California Agriculture.

DOI

Samuel N Araya, Fryjoff-Hung, A., Anderson, A., Viers, J. H., Ghezzehei, T. A. (2021). Advances in Soil Moisture Retrieval from Multispectral Remote Sensing Using Unmanned Aircraft Systems and Machine Learning Techniques. Hydrology and Earth System Sciences.

DOI

Samuel N Araya, Fryjoff-Hung, A., Anderson, A., Viers, J. H., Teamrat A Ghezzehei (2020). Machine Learning Based Soil Moisture Retrieval from Unmanned Aircraft System Multispectral Remote Sensing. IEEE International Geoscience and Remote Sensing Symposium.

DOI

Samuel N Araya, Teamrat A Ghezzehei (2019). Using Machine Learning for Prediction of Saturated Hydraulic Conductivity and Its Sensitivity to Soil Structural Perturbations. Water Resources Research.

Project DOI

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