M.Sc.

Kostiantyn Lavronenko

Guest Researcher

 140
 +49 241 80 27865
 Kostiantyn.Lavronenko@lfb.rwth-aachen.de



Curriculum Vitae

Work Experience

September 2024- Present Fraunhofer MEVIS Research Scientist
Development of low-field MRI system with inhomogenity optimisation and enhanced image reconstruction
November 2022 – August 2024 Infineon Technologies
(part-time, working student)
Machine Learning Researcher
– Development of a Deep Learning algorithm for anomaly detection and classification on radar signal data
– Development of a data pipeline for an algorithm-based API
October 2019 – October 2022 Futavis GmbH
(part-time, working student)
Embedded Software Developer
– Development of a simulation environment for embedded system testing of a Battery Management System

 

Education

October 2021 – August 2024 RWTH Aachen, M.Sc. Data Science, Focus Area: Computer Science
February 2017 – September 2021 RWTH Aachen, B.Sc. Physics

Research Fields

  • My research focuses on the development of low-field MRI technology, with a particular emphasis on improving image reconstruction methods through the use of computer vision, machine learning, and optimization algorithms. Currently, I am simulating the MRI system in a virtual environment, optimizing magnetic field inhomogeneities using advanced computational techniques such as genetic algorithms. The potential application of reinforcement learning is also being explored at this stage. This work combines elements of physics, data analysis, and optimization techniques to fine-tune system performance.

Thesis Topics

 

Publications

 

Journal Publications

2024

Fusco, Alessandra, Sakharov, Sviatoslav, Lavronenko, Kostiantyn, Hazra, Souvik, Servadei, Lorenzo, Wille, Robert
Deep Learning Classifier for Robust Artifact Rejection in FMCW Radar Vital Sensing
In: IEEE Sensors Journal

Conference Publications

2024

Lavronenko, K., Paiva, L. Lopes de, Mueller, F., Schulz, V. and Naunheim, S.
Towards artificial data generation for accelerated PET detector ML-based timing calibration using GANs
In: 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)