Nemanja Milošević

PhD - Computer Scientist
Assistant Professor, Department of Mathematics and Informatics, Novi Sad, Serbia


Spring semester 2022/2023

Consultations are online this semester, on the Cisco Webex platform
Contact me via email, for scheduling:


All course information is hosted on e-PMF Moodle portal.
Deep Learning
Moodle - Deep Learning
Distribuirano duboko učenje
Moodle - Distributed Deep Learning

Business Software Development
Moodle - Business Software Development

Scientific Programming
Moodle - Scientific Programming

Mobile Application Development
Professor: dr Danijela Tešendić
Moodle - Mobile Application Development


Google Scholar

  • SUKUR, N., MILOŠEVIĆ, N., PEŠIĆ, S., KOLEK, J., RAKIĆ, G., & BUDIMAC, Z. (2016). First Results of WCET Estimation in SSQSA Framework. In Fifth Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications SQAMIA 2016 (p. 81).
  • MILOŠEVIĆ, N., BOBERIĆ KRSTIĆEV D. & RACKOVIĆ, M. (2017) From traditional to containerized system architecture: SCLIT 2017: 7th Symposium on Computer Languages, Implementations and Tools
  • ARAPAKIS et al., "Towards Specification of a Software Architecture for Cross-Sectoral Big Data Applications," 2019 IEEE World Congress on Services (SERVICES), Milan, Italy, 2019, pp. 394-395. doi: 10.1109/SERVICES.2019.00120
  • MILOŠEVIĆ N. ., RACKOVIĆ, M. (2019) Classification based on missing features in Deep Convolutional Neural Networks, Neural Network World Journal (University of Prague) Volume 29 pp. 221-234 doi: 10.14311/NNW.2019.29.015
  • MILOŠEVIĆ, N. , RACKOVIĆ, M. (2020) Synergy between traditional classification and classification based on negative features in deep convolutional neural networks. Neural Computing and Applications, November 2020, doi: 10.1007/s00521-020-05503-4
  • Bakhtiarnia, A., Milošević, N., Zhang, Q., Bajović, D., Iosifidis, A. (2022). Dynamic split computing for efficient deep edge intelligence. arXiv preprint arXiv:2205.11269. ICML Workshop on Dynamic Neural Networks, 2022, WA, USA
  • Milosevic, N., Jakovetic, D., Skrbic, S., Savic, M., Stamenkovic, D., Mascolo, J., Masera, D. (2022, August). BACS: A comprehensive tool for deep learning-based anomaly detection in edge-fog-cloud systems. In 2022 30th European Signal Processing Conference (EUSIPCO) (pp. 1097-1101). IEEE.
  • Bravos, G., Cabrera, A. J., Correa, C., Danilović, D., Evangeliou, N., Ezov, G., ... Milosevicn, N., Vukobratovic, D. (2022). Cybersecurity for industrial Internet of Things: architecture, models and lessons learned. IEEE Access, 10, 124747-124765.
  • Jakovetic, D., Bajovic, D., Sahu, A. K., Kar, S., Milosevic, N., Stamenkovic, D. (2022). Nonlinear gradient mappings and stochastic optimization: A general framework with applications to heavy-tail noise. arXiv preprint arXiv:2204.02593.

Open Source

Fedora Project
Fedora Project Developer & Ambassador



Curriculum Vitae

Last update: January 2023.

CV - English