People

Gordan Mimić

Gordan Mimic

Position:Senior research associate in CST

Academic Rank: Senior research associate

Google Scholar

Gordan Mimić is a Senior Research Associate at BioSense Institute. Gordan Mimić received BSc (2011), MSc (2012) and PhD (2016) degrees in Physics-Meteorology at the University of Novi Sad, Faculty of Sciences. He was working at Republic Hydrometeorological Service of Serbia during the period 2011-2012, in the division for Numerical Weather Prediction. Gordan Mimić was teaching assistant for the various courses in meteorology at the University of Novi Sad (Faculty of Sciences and Faculty of Agriculture) in the period 2012-2017. His current research interest is predictive analytics in the field of agrometeorology. He was the leader of the BioSense team that developed a novel algorithm for the classification of maize hybrids tolerant to drought and heat stress, which won the third prize at Syngenta Crop Challenge in Analytics 2019. He participated in several national and international projects. Gordan Mimić has co-authored 33 journal articles, 26 conference papers, 3 technical solutions and 1 book chapter.

Center:

proba 2

CIT

Themes:

1. Machine Learning

2. Big Data Analytics

3. Knowledge discovery

4. AgroSense

5. Government

Publications:

  1. Mimić, G., Mishra, A.K., Marković, M., Živaljević, B., Pavlović, D., Marko, O. Machine Learning-Based Harvest Date Detection and Prediction Using SAR Data for the Vojvodina Region (Serbia). Sensors 25(7), 2239 (2025). https://doi.org/10.3390/s25072239
  2. Mimić, G., Podraščanin, Z., Basarin, B. Change detection of the Köppen climate zones in Southeastern Europe. Atmospheric Science Letters 25 (11), e1270 (2024) https://doi.org/10.1002/asl.127010
  3. Mimić, G., Živaljević, B., Blagojević, D., Pejak, B., Brdar, S. Quantifying the Effects of Drought Using the Crop Moisture Stress as an Indicator of Maize and Sunflower Yield Reduction in Serbia. Atmosphere 13(11), 1880 (2022) doi.org/10.3390/atmos13111880
  4. Maestrini, B., Mimić, G., van Oort, P.A.J., Jindo, K., Brdar, S., Athanasiadis, I., van Evert, F.K. Mixing process-based and data-driven approaches in yield prediction, European Journal of Agronomy 139, 126569 (2022) doi.org/10.1016/j.eja.2022.126569
  5. Filipović, N., Brdar, S., Mimić, G., Marko, O., Crnojević, V. Regional soil moisture prediction system based on Long Short-Term Memory network, Biosystems Engineering 213, 30-38 (2022) doi.org/10.1016/j.biosystemseng.2021.11.019