Hind Hallabia | Data Science | Excellence in Research Award

Dr. Hind Hallabia | Data Science | Excellence in Research Award

Teaching and Researcher Assistant | University Institute of Technology of Saint Etienne Jean Monnet University | France

Dr. Hind Hallabia, affiliated with the University Institute of Technology of Saint-Étienne at Jean Monnet University, France, specializes in remote sensing, pansharpening, and advanced image processing techniques for satellite data analysis. Her research focuses on developing graph-based segmentation methods, superpixel modeling, and data fusion frameworks to enhance multispectral and panchromatic imagery. Dr. Hallabia investigates latent low-rank decomposition, detail-injection mechanisms, and texture-based segmentation models to improve image quality, spatial–spectral fidelity, and analytic accuracy in Earth observation applications. Her work contributes to advances in hazardous-area monitoring, environmental assessment, and optical remote sensing technologies through methodological innovation, algorithm design, and computational enhancements.

Profiles: Scopus | Orcid

Featured Publications

  • Hallabia, H. (2025). A graph-based superpixel segmentation approach applied to pansharpening. Sensors, 25(16), Article 4992. https://doi.org/10.3390/s25164992
    Year: 2025

  • Hallabia, H. (2025). Land and aquatic spectral signatures analysis over a spatio-temporal hazardous area acquired by Worldview satellite. Annual International Congress on Electrical Engineering 2025.
    Year: 2025

  • Hallabia, H. (2025). Advanced trends in optical remotely sensed data fusion: Pansharpening case study. Iris Journal of Astronomy and Satellite Communications.
    Year: 2025

  • Hallabia, H., Hamam, H., & Ben Hamida, A. (2023). A novel detail injection framework using latent low-rank decomposition for multispectral pan-sharpening. Multimedia Tools and Applications, 82, 11971–11995. https://doi.org/10.1007/s11042-022-12770-x
    Year: 2023

  • Hallabia, H., & Hamam, H. (2021). A graph-based textural superpixel segmentation method for pansharpening application. Proceedings of IGARSS 2021. https://doi.org/10.1109/igarss47720.2021.9553304
    Year: 2021

Milica Milovanović | Operations Research | Excellence in Research Award

Prof. Milica Milovanović | Operations Research | Excellence in Research Award

Master Transportation Engineer | Faculty of Transport and Traffic Engineering, University of Belgrade | Serbia

Prof. Milica Milovanović, affiliated with the Faculty of Transport and Traffic Engineering at the University of Belgrade, specializes in transport safety, risk analysis, and decision-making methodologies in aviation and road traffic systems. Her research focuses on evaluating the Value of Statistical Life (VSL) in transport accidents, optimizing safety measures in aviation operations, and conducting risk assessments involving UAVs, drones, and logistics systems.
She frequently applies advanced multi-criteria decision-making (MCDM) models, hybrid assessment techniques, and quantitative risk frameworks. Her work contributes to improved safety policies, evidence-based investment decisions, and the development of safer, more efficient air and road transport systems.

Profiles: Scopus | Orcid

Featured Publications

Milovanović, M., Vujačić Petrović, J., Čokorilo, O., Vasov, Lj., Mirosavljević, P. D., & Stojiljković, B. (2025). Analysis of the value of statistical life in traffic accidents based on investments evaluation. Tehnika. https://doi.org/10.5937/tehnika2502223M

Snežana Tadić, Milovanović, M., Krstić, M., & Čokorilo, O. (2025). Selection of safety measures in aircraft operations: A hybrid Grey Delphi–AHP–ADAM MCDM model. Eng. https://doi.org/10.3390/eng6110295

Milovanović, M., Čokorilo, O., Ivković, I., Stojiljković, B., & Vasov, Lj. (2024). The value of statistical life in air and road transport. Aircraft Engineering and Aerospace Technology. https://doi.org/10.1108/aeat-01-2024-0019

Marina, M., Čokorilo, O., Mirosavljević, P., Vasov, Lj., Stojiljković, B., & Milovanović, M. (2024). Analysis of the impact of UAV collision on a commercial aircraft. In 2024 6th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). https://doi.org/10.1109/summa64428.2024.10803713

Tadić, S., Krstić, M., Veljović, M., Čokorilo, O., & Milovanović, M. (2024). Risk analysis of the use of drones in city logistics. Mathematics, 12(8), 1250. https://doi.org/10.3390/math12081250