Sergii Skakun

Sergii Skakun

Assistant Professor

Dr. Sergii Skakun is an Assistant Professor with a joint appointment at the Department of Geographical Sciences and the University of Maryland College of Information Studies (UMD iSchool). He joined UMD in October 2015. From 2013 to 2015, he was a Senior Engineer at Samsung SDI (South Korea), where he was responsible for developing industrial vision inspection systems. From 2006 to 2013, he has held multiple positions (latest Senior Scientist) at the Space Research Institute (Ukraine), where he was performing research in remote sensing. He received a PhD in Computer Science from National Academy of Sciences of Ukraine in 2005.

Dr. Skakun have participated as a PI or Co-I in projects funded by NASA, Google, European Commission (EC), EC Joint Research Center (JRC), U.S. Civilian Research & Development Foundation (CRDF), National Academy of Sciences of Ukraine, State Space Agency of Ukraine and Science & Technology Center in Ukraine (STCU). He is currently a PI on several NASA funded projects, namely “Crop yield assessment and mapping by a combined use of Landsat-8, Sentinel-2 and Sentinel-1 images”, “Maintenance and refinement of the Suomi NPP VIIRS Land Surface Reflectance product suite”, and “Open-Source Deep Learning Classification and Visualization of Multi-Temporal Multi-Source Satellite Data”. From 2005 to 2013, he was a member of the Working Group on Information Systems and Services (WGISS) of the Committee of Earth Observation Satellites (CEOS), where he was involved in developing the SensorWeb technology for disaster monitoring and risk assessment. He is currently an Associate Editor for the journal AIMS Geosciences (section: Computing Sciences for Environment) and Section Editorial Board Member for the journal Remote Sensing (section: Remote Sensing Image Processing). As of 2019, he authored or co-authored 42 papers in peer-reviewed journals.


My focus is to advance methods, models and emerging technologies in the area of data science for heterogeneous remote sensing data fusion, processing and analysis, and their applications to Earth System Science and areas of societal benefit.


  • Remote sensing
  • Agricultural monitoring
  • Machine learning in remote sensing
  • Disaster monitoring and risk assessment


  • Ph.D. in Computer Science, National Academy of Sciences of Ukraine

  • M.S. in Applied Mathematics (with honors), National Technical University of Ukraine “Kyiv Polytechnic Institute
Associated Research Centers