Work Experience
Assistant Researcher, Research Center for Spatial Information (CEOSpace Tech) 2020 - 2023 (Expected)
Earth Observation, SAR, AI, Deep Learning, Machine Vision, Python
Assistant Researcher and PhD student at the University POLITEHNICA of Bucharest (UPB), Research Center for Spatial Information (CEOSpaceTech), Bucharest, Romania, in the frame of the MENELAOS-NT European Training Network (ETN) H2020-MSCA-ITN project. The MENELAOS-NT project applies novel technologies to realize multimodal – multi-sensor data fusion to optimally combine the information, delivered by different sensors (in-situ/remote, optical/non-optical) on different scales, with different resolutions, and with different reliability. My main focus in this project was on the development of various deep learning-based solutions for Synthetic Aperture Radar (SAR) data applications.
Study the fundamentals of SAR imaging systems and image formation.
Elaboration of deep learning-based solutions for various applications of SAR data, such as data compression, land cover classification, and semantic data mining.
Development of the complex-valued deep architectures for complex-valued SAR data.
Development of the complex-valued SAR dataset for the training of the deep architectures, S1SLC-CVDL dataset.
Researcher, Research Center for Spatial Information (CEOSpace Tech) - ARTISTE Project 2022 - 2023
Earth Observation, SAR, AI, Deep Learning, Compression, Python
Key personnel and researcher at the Artificial Intelligence for SAR Data Compression (ARTISTE) project. The project is funded by European Space Agency (ESA) and aims to provide artificial intelligent-based solutions for SAR raw data compression for future ESA missions in collaboration with DLR and Airbus teams.
Contribution to writing the project proposal.
Development of deep-learning-based compression methods for SAR data compression.
Visiting Researcher, Zentrum für Sensorsysteme (ZESS) 2021 - 2022
Earth Observation, SAR, AI, Deep Learning, Machine Vision, Python
Research secondment at the University of Siegen, Zentrum für Sensorsysteme (ZESS), Germany, in the frame of the MENELAOS-NT European Training Network (ETN) H2020-MSCA-ITN project. The main focus of the secondment was on the development of the complex-valued deep architectures for SAR data classification and the comparison between complex- and real-valued architectures.
Development of complex-valued deep architectures.
compartive study between the complex- and real-valued deep architectures for SAR data classification.
Presentation of the results in various conferences and forums, including IGARSS 2022, EuSAR 2022, and MENELAOS Forum 2022.
Researcher, Remote Sensing Lab, K.N. Toosi University of Technology 2016 - 2018
Earth Observation, SAR, Machine Vision, Python
Master student and researcher at the Remote Sensing lab of the faculty of Geodesy & Geomatics Engineering, K.N. Toosi University of Technology. The main focus of my research was development of machine learning algorithms for SAR data classification.
Development of Segment-based Bag of Visual Words (BOVW) method for enhancment of SAR data classification.
Master’s research thesis
Source code
