Ievgen Voloshenko

Ievgen Voloshenko, PhD, is a Machine Learning Engineer and Deep Learning Engineer at ROSEN since August 2019, specializing in the automation of visual non-destructive pipeline inspection tools and the integration of real-time deep neural network object detection algorithms on edge systems. Previous experience includes serving as Team Lead Robotics, where Ievgen developed an autonomous agent for oil tank storage integrity assessment and implemented various technologies such as lidar-based SLAM and active camera object detection. Prior to ROSEN, Ievgen worked as a Doctoral Student/Scientific Employee at the University of Stuttgart, focusing on plasmonic nanostructures and light depolarization properties, and as a Scientific Assistant involved in data analysis and visualization for FTIR and ellipsometric measurements. Educational qualifications include a PhD in Nanophotonics, a Master's in Condensed Matter and Materials Physics, and a Bachelor's in Physics.