Amanda Ramcharan

  • ABE Graduate Assistant, Ph.D.
Amanda Ramcharan
108 Research Unit A
University Park, PA 16802
Work Phone: 814-865-4071

Areas of Expertise

  • digital soil mapping
  • machine learning algorithms
  • data mining
  • soil property modeling
  • biophysical modeling


  1. B.S.E., Mechanical Engineering, Certificate in the Program in Sustainable Energy, Princeton University, 2011
I'm a PhD candidate in Agricultural Engineering working with Armen Kemanian and Tom Richard to develop quantitative engineering tools to address challenges of agriculture, environment, and development. I am also pursuing a minor in Computational Science through the Aerospace Engineering department at Penn State.

My previous research experience includes modeling crop growth and yield as well as carbon and nitrogen fluxes in innovative bioenergy cropping systems.  By incorporating winter “double crops” as energy crops on land that would otherwise be fallow for roughly 8 months of the year, my results have shown that these systems can both increase productivity and reduce nutrient pollution, and challenges prior assumptions about food and biofuel conflicts on agricultural land. 

My current research merges the knowledge paradigm of soil scientists with machine learning algorithms to address one of the grand challenges of soil science, to gain a better understanding of the three-dimensional distribution of soil properties across the continental US. Soils are at the interface of land-water-atmosphere, thus soils act as the heart of functioning ecosystems. Although soil looks two dimensional, its functionality primarily occurs through processes that occur in the third dimension, referred to as the soil profile. Characterizing the soil profile is a time-consuming, expensive task therefore my research seeks to couple the largest national database of soil profiles, the NCSS Soil Characterization Database, to spatial environmental variables representing theories of soil genesis and morphology to produce a continuous 3-D national soils database. The applications of this product include an inventory of the US soil carbon stocks, to robust soil databases that can support ecosystem simulation models used to assess the quality of soil, air, and water. 

My inspiration to address challenges in the agricultural field (no pun intended) comes from my experience working in Kenya in the Princeton in Africa program for Nyumbani Village, a non-profit pursuing a path of sustainable development for local food and water resources. Originally from Trinidad and Tobago, I'm also deeply interested in agricultural challenges in developing countries.


Thomas Richard, Armen Kemanian