Solomiia Kurchaba
Guest Postdoc
- Name
- S. Kurchaba MSc
- Telephone
- +31 71 527 2727
- s.kurchaba@liacs.leidenuniv.nl
Solomiia Kurchaba is a postdoc at Leiden Institute of Advanced Computer Science. She joined Leiden University in May 2020. She obtained her MSc degree in Theoretical Physics from University of Silesia in Katowice (Poland).
More information about Solomiia Kurchaba
Solomiia Kurchaba is a postdoc at Leiden Institute of Advanced Computer Science. She joined Leiden University in May 2020. She obtained her MSc degree in Theoretical Physics from University of Silesia in Katowice (Poland). After obtaining her MSc, she worked as a Data Scientist at StorkJet sp. z o.o., also in Katowice. There her work was focused on the development of machine learning-based projects for aircraft performance monitoring.
In her PhD, she worked on the Algorithms for the Verification of Emissions from Shipping with Satellites (AVES-oculuS) project for the Inspectorate for Human Environment and Transport (ILT) of the Netherlands. The research is focused on analysis of S5P-TROPOMI satellite measurements together with AIS data of ship positions for an estimation of NO2 emission produced by individual seagoing vessels.
Guest Postdoc
- Science
- Leiden Inst of Advanced Computer Science
- Kurchaba S. (11 June 2024), Machine learning-based NO2 estimation from seagoing ships using TROPOMI/S5P satellite data (Dissertatie. Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University). Supervisor(s) and Co-supervisor(s): Verbeek F.J. & Meulman J.J., Veenman C.J.
- Kurchaba S., Vliet J. van, Verbeek F.J. & Veenman C.J. (2023), Anomalous NO2 emitting ship detection with TROPOMI satellite data and machine learning, Remote Sensing of Environment 297: 113761.
- Kurchaba S., Vliet J. van, Verbeek F.J., Meulman J.J. & Veenman C.J. (2022), Supervised segmentation of NO2 plumes from individual ships using TROPOMI satellite data, Remote Sensing 14(22): 5809.
- Kurchaba S., Vliet J. van, Meulman J.J., Verbeek F.J. & Veenman C.J. (2021), Improving evaluation of NO2 emission from ships using spatial association on TROPOMI satellite data. Meng X., Wang F., Lu C.T., Huang Y., Shekhar S. & Xie X. (Eds.), Proceedings of the 29th International Conference on Advances in Geographic Information Systems. SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems 2 November 2021 - 5 November 2021. New York, U.S.A.: ACM. 454-457.