Vladimir Kazei is a research scientist at Seismic Wave Analysis Group at KAUST. Vladimir’s research is focused on deep learning applications to seismic inverse problems. He obtained his PhD degree in geophysics from St. Petersburg State University in 2016, sponsored by Shell GSI BV and SEG scholarship (2015). Vladimir has over 30 publications in peer-reviewed international journals and conference proceedings focused on seismic imaging for exploration geophysics.
Vladimir is the winner of NVIDIA-KAUST GPU hackathons 2017 & 2019. He pioneered deep learning-based low frequency extrapolation for full-waveform inversion in 2017 and released one of the first open-source projects on deep learning-based velocity model building in 2019.