Oskar Marko
Position:Head of the Center for Information Technologies
Academic Rank: Research Associate in the field of technical/technological sciences-electronics, telecommunications, and information technologies
Oskar Marko, Ph.D. is the Head of the Center for Information Technologies and the Assistant Director for Innovation and Cooperation with the Economy at the BioSense Institute. His research focuses on applying advanced machine learning and evolutionary algorithms in agriculture. He spent the 3rd year of his undergraduate studies at City University London, where he did his final BEng project in signal processing. He led BioSense’s team that developed novel Big Data algorithms for yield prediction, seed distribution, and optimization of sowing strategies, which secured the 1st prize for BioSense at the Syngenta Crop Challenge and CGIAR Inspire Challenge. He is actively involved in many Horizon 2020 projects including Antares, Cybele, Dragon, and Flexigrobots, and industrial projects with partners such as Krivaja, MK Agriculture, Delta, and other farming and insurance companies.
Center:
CIT
Themes:
1. Machine Learning
2. Deep Learning
3. Big Data Analytics
4. Knowledge discovery
5. Sentinel Data Hub
6. Satellite imaging
7. Drone Imaging
8. Robotics
9. Hyperspectral, Multispectral and Thermal Imaging
10. Geospatial data analytics
11. AgroSense
12. New technologies are restoring the trust between producers and insurance companies
13. Government
Projects:
Publications:
- Marko, O., Brdar, S., Panić, M., Šašić, I., Despotović, D., Knežević, M., & Crnojević, V. (2017). Portfolio optimization for seed selection in diverse weather scenarios. PloS one, 12(9), e0184198.
- Marko, O., Brdar, S., Panic, M., Lugonja, P., & Crnojevic, V. (2016). Soybean varieties portfolio optimisation based on yield prediction. Computers and Electronics in Agriculture, 127, 467-474.
- Marko, O., Pavlović, D., Crnojević, V., & Deb, K. (2019, July). Optimisation of crop configuration using NSGA-III with categorical genetic operators. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 223-224).
- Šikoparija, B., Marko, O., Panić, M., Jakovetić, D., & Radišić, P. How to prepare a pollen calendar for forecasting daily pollen concentrations of Ambrosia, Betula and Poaceae?. Aerobiologia, 1-15.
- O Marko, M Panić, P Lugonja, G Kitić, S Birgermajer, N Ljubičić, V Radonić, Software tool for smart irrigation based on machine learning, 2019
Patent:
- A method for early prediction of wheat yield based on artificial intelligence