Resume

PhD Candidate in Precision Agriculture & Artificial Intelligence | Remote Sensing | Machine Learning

Summary

Jitender Rathore

PhD candidate (Virginia Tech) specializing in Precision Agriculture, Remote Sensing, and AI-driven crop yield prediction. Experienced with satellite/UAV data, machine learning (RF, SVM, CNN, LSTM), and geospatial analytics for agriculture and environmental monitoring.

  • Blacksburg, Virginia, USA
  • (+1) 757 957 3628
  • jitenderr15@vt.edu
  • linkedin.com/in/jitenderrathore93

Education

PhD – Precision Agriculture & Artificial Intelligence

2022 – Present

Virginia Tech, USA

Advisors: Dr. Olga S. Walsh, Dr. Maaz Gardezi

Master of Science – Geospatial Science

2019 – 2021

University of Twente (ITC), Netherlands

Thesis: Detecting ratoon rice using Sentinel-1 time series + machine learning.

Master of Science – Remote Sensing and GIS (Gold Medalist)

2017 – 2019

Kumaun University, India

Thesis: Remote-sensing investigation of NCR air pollution during post-monsoon season.

Bachelor’s in Geography

2014 – 2017

University of Delhi, India

Professional Experience

Agricultural & Remote Sensing Technician

2018 – 2020

6th Grain Global Corporation, Bangalore (Maryland, USA based)

  • Analyzed crop patterns using satellite data, NDVI, and crop calendars.
  • Conducted field-level and regional GIS/RS assessments.
  • Prepared geospatial visualizations and analytical reports.
  • Worked independently with international teams in a remote setting.

Honors & Awards

  • CALS Travel Grant – AGU 2025 ($750)
  • SPES Travel Grant – AGU 2025 ($750)
  • TPSC Student Grant 2025 – $3000
  • ITC Excellence Scholarship (2019–2021)
  • CSSS Scholarship (2015–2019)

Competitions

  • World Bank Data4SoilHealth Global Summit Finalist (2025)
  • 3rd Place - AgAID Agathon, Washington State University (2023)

Skills

  • Programming: Python, R, SQL, GEE
  • Remote Sensing: Sentinel-1/2, Landsat, UAV imaging
  • GIS Tools: QGIS, ArcGIS
  • Machine Learning: RF, SVM, CNN, LSTM, Spatial ML
  • Geospatial Analytics: Raster/Vector processing, spatial statistics