Vitaliy Kinakh


Vitaliy Kinakh received a BS in Applied Mathematics degree and  MSc in Mathematical and Computer modeling and from Lviv Polytechnic National University in 2020 and 2021. He was working as a consultant, engineer, and researcher in the areas of Computer Vision, Machine Learning, Deep Learning, and Remote Sensing both in private industry and academia.

Research interests

  • Current research directions:
    • Self/semi-supervised learning
    • Generative models
    • Data-Efficient Deep Learning
    • Computer vision: deep learning for image processing, recognition, compressive sensing
  • Previous research:
    • Remote sensing: analysis of raster data on GHG emissions and nighttime light, deep learning for remote sensing (BS, MS, collaboration with IIASA, NASA and Universities Space Research Association (USRA))
    • Optimization and operational research (Internship at Laval University, Quebec, Canada)


Teaching assistant for:


See at Google Scholar