Ms. Sofiia Drozd | Remote Sensing | Best Researcher Award

Ms. Sofiia Drozd, Remote Sensing, Best Researcher Award

Sofiia Drozd at National Technical University of Ukraine, Ukraine

Professional Profile

๐ŸŒŸย Summary:

Sofiia Drozd is a dedicated Master’s student at NTUU KPI, specializing in Mathematical Modeling and Data Analysis, and a researcher at the Space Research Institute NASU-SSAU. Her expertise spans machine learning, remote sensing, and satellite data processing, with significant contributions to global projects supported by organizations like the World Bank and Horizon Europe. Sofiia’s research focuses on developing algorithms for environmental monitoring, land use analysis, and renewable energy assessment. She actively contributes to Ukraine’s energy sector recovery and agricultural damage assessment efforts, aiming to restore stability and sustainability in both domains.

๐ŸŽ“ Education:

Master’s student in Mathematical Modeling and Data Analysis, NTUU KPI

๐Ÿ’ผ Professional Experience:

Researcher, Space Research Institute NASU-SSAU

๐Ÿ”ฌ Research Areas:

  • AI and machine learning
  • Remote sensing
  • Satellite data processing
  • GIS

๐Ÿ“– Publications Top Noted:

Paper Title: Solar energy potential mapping in Ukraine through integration of GIS, remote sensing, and fuzzy logic
  • Authors: Sofiia Drozd, Nataliia Kussul
  • Journal: European Journal of Remote Sensing
  • Year: 2024
Paper Title: Evaluating the Impact of Armed Conflict on Agricultural Sector in Ukraine through Remote Sensing and Machine Learning
  • Authors: Sofiia Drozd, Nataliia Kussul, Hanna Yailymova
  • Year: 2024
Paper Title: War damage detection based on satellite data
  • Authors: Andrii Shelestov, Sophia Drozd, Polina Mikava, Illia Barabash, Hanna Yailymova
  • Year: 2023
  • Citations: 5
Paper Title: Assessing damage to agricultural fields from military actions in Ukraine: An integrated approach using statistical indicators and machine learning
  • Authors: Nataliia Kussul, Sofiia Drozd, Hanna Yailymova, Andrii Shelestov, Guido Lemoine, Klaus Deininger
  • Journal: International Journal of Applied Earth Observation and Geoinformation
  • Year: 2023
  • Citations: 3
Paper Title: Generative adversarial network augmentation for solving the training data imbalance problem in crop classification
  • Authors: Leonid Shumilo, Anton Okhrimenko, Nataliia Kussul, Sofiia Drozd, Oleh Shkalikov
  • Year: 2023
  • Citations: 3