Experience

Independent Researcher & Contract Lecturer

University of Pavia - Telecommunications & Remote Sensing Laboratory

Published peer-reviewed research achieving 93.3% accuracy in rice paddy mapping across 732,345 hectares in Telangana, India.

Teaching:

  • Contract lecturer: Remote Sensing for Agricultural Applications (12 hours)
  • Pre-course instructor: Essential Skills for Remote Sensing and Geomatics (12 hours)
  • Seminar series: Remote Sensing Applications - Theory to Practice (12 hours)

Research Focus:

  • Advanced machine learning for agricultural monitoring
  • Multi-temporal satellite imagery analysis
  • Phenology-based crop classification

Junior Data Analyst

eTek IT Services, Inc.

  • Implemented ETL processes using IBM DataStage for legacy system integration
  • Developed interactive Tableau dashboards for business metrics visualization
  • Performed statistical analysis identifying trends driving business strategy
  • Collaborated with data scientists on predictive model development

Research Intern

CBK PAN Space Research Center

Thesis project: Paddy Field Mapping in Nalgonda District using Sentinel-2 imagery in Google Earth Engine. Developed novel methodology achieving 90% accuracy in rice field classification with machine learning algorithms and spectral indices.

Education

MSc Electronics Engineering (Space Communication & Sensing)

University of Pavia

Specialized in space communications and remote sensing. Thesis work on rice paddy mapping using multi-temporal Sentinel-2 imagery achieved 90% classification accuracy.

BTech Electronics and Communications Engineering

JNTUH College of Engineering Hyderabad

Bachelor’s degree in Electronics and Communications Engineering from Jawaharlal Nehru Technological University Hyderabad.
Skills & Hobbies
Geospatial & Remote Sensing
Google Earth Engine
Sentinel-2 Imagery Analysis
QGIS / ArcGIS
Programming & ML
Python
Machine Learning (scikit-learn)
Data Analysis (Pandas, NumPy)
Visualization & Reporting
Tableau
Matplotlib / Seaborn
Streamlit
Awards
Published Research in Environmental Challenges
Elsevier ∙ January 2025
Satellite-based Rabi rice paddy field mapping in India achieving 93.3% accuracy across 732,345 hectares. DOI: 10.1016/j.envc.2025.101320
Languages
100%
English Professional
60%
Italian Intermediate (B1)
80%
Hindi Professional