Experience

Enriched Ag

• United States
• Information Technology & Services
• 1 - 100 Employee

• Senior Research Scientist

  • Nov 2021 - Present

  Be more resilient and profitable with our grazing, carbon and beef supply chain data. Be more resilient and profitable with our grazing, carbon and beef supply chain data.



Michigan State University

• United States
• Higher Education
• 700 & Above Employee

• Research Scientist - Geospatial Data and Machine Learning

  • Oct 2019 - Oct 2021

  Data-driven Agriculture, Geospatial Modeling, Machine Learning I combine satellite and drone imagery, machine learning algorithms and process-based crop models to understand agricultural systems, to predict the impact of climate, soil and management on crop yield, nutrient uptake, and water use efficiency, and ultimately, to inform management decisions for sustainable agricultural production. Overall goal is to enable smarter solutions for precision agriculture in a resource-constrained and rapidly-changing world. I am involved in developing and implementing data science and machine learning models in variety of applications, including: 1) Developing and applying image classification and multi-level (supervised and unsupervised) machine learning algorithms for cloud and shadow detection in satellite imagery. 2) Timeseries prediction of vegetation health from satellite imagery using historical change, geospatial data, soil and topography information. 3) Integration of process-based crop models and machine learning models for large-scale yield and soil organic carbon prediction using soil, historical weather, and farm management data. 4) Developing algorithms for canopy cover estimation and plant growth prediction from greenhouse (leafy greens) images using image segmentation and machine learning. 5) Mapping crop growth, spacing and vegetation health from UAV imagery using image segmentation and edge detection algorithms. Show less



Great Lakes Bioenergy Research Center (GLBRC)

• United States
• Biotechnology Research
• 1 - 100 Employee

• Research Scientist

  • Oct 2019 - Oct 2021

  Data science and machine learning application in precision agriculture and geospatial modeling Data science and machine learning application in precision agriculture and geospatial modeling



Croptix

• United States
• Farming
• 1 - 100 Employee

• Consultant, Data Scientist (Machine Learning)

  • 2017 - 2018

  - Processed sensor data and developed machine learning models to detect early drought stress, nutrient (nitrogen, phosphorus) deficiency, and disease pressure in agricultural crops. - ML models implemented for classifying spectral features are weighted k-nearest neighbor, decision tree, linear and quadratic discriminant analysis, support vector machine, ensemble models, and artificial neural network models. - Developed GIS-based visualizations and customized software tools to derive actionable insights from agricultural data, particularly to inform water and nutrient management decisions. Show less



Penn State University

• United States
• Higher Education
• 700 & Above Employee

• Postdoctoral Research Associate

  • 2015 - 2018

  - Analyzed the effects of climate variability, crop irrigation demand and streamflow on groundwater level fluctuations and future water availability across major agricultural regions of United States. (Collaboration with Center for Robust Decision Making on Climate and Energy Policy (RDCEP), University of Chicago). - Designed predictive models based on machine learning algorithms (neural networks, genetic algorithm), regression models, spectral analysis, mutual information and Monte Carlo uncertainty analysis technique to better understand these interactions. - Developed simulation models using high performance computing including parallel simulation and large (netcdf) dataset analysis and manipulation. - Developed classification models based on spectral signatures and machine learning algorithms to detect early drought stress, nutrient deficiency and disease pressure in agricultural crops (Collaboration with Atoptix, State College, PA). - Simulated groundwater depletion model for India using physical and economic factors with a particular focus on impacts of policy and possible reform pathways (Collaboration with Johns Hopkins, Energy, Resources and Environment, Washington, DC). Show less