Prof. dr Žarko Ćojbašić

Žarko Ćojbašić is a full professor of the Mechanical Engineering Faculty, University of Niš, Serbia and is affiliated with its Department of Mechatronics and Control. He is a Senior Member of IEEE and currently acting as an elected Chair of the Computational Intelligence Chapter of IEEE Serbia and Montenegro Section. He was a coordinator and participant of numerous research and educational projects, and within projects and research grants he stayed at several European universities such as Technical University of Berlin Germany, University of Vigo Spain, Imperial College London UK, University of Bremen Germany, University of Exeter UK, Polytechnic University of Catalonia Barcelona Spain, and others. His research interests include control systems and robotics, intelligent control systems, computational intelligence, mechatronics and biomedical engineering. He has published nearly 80 papers in journals from  SCI list, while his citation indexes are h=23 at SCOPUS and h=24 at Google Scholar. Professor Žarko Ćojbašić is currently acting as a contracted European Union expert in the fields of robotics, control, computational intelligence and biomedical engineering.

Жарко Ћојбашић је редовни професор Машинског факултета Универзитета у Нишу, Србија, а члан је Катедре за мехатронику и управљање. Он је сениор члан највећег светског професионалног удружења инжењера IEEE и тренутно обавља функцију изабраног председника Друштва за вештачку интелигенцију IEEE секције за Србију и Црну Гору. Био је координатор и учесник бројних научних, истраживачких и образовних пројеката, а у оквиру пројеката и истраживачких грантова боравио је на многим европским универзитетима, као што су Технички универзитет у Берлину – Немачка, Универзитет у Вигу – Шпанија, Империал Колеџ Лондон и Универзитет у Ексетеру – Велика Британија, Универзитет у Бремену – Немачка, Политехнички универзитет Каталоније у Барселони – Шпанија и другим. Његови истраживачки интереси укључују управљање системима и роботику, интелигентне системе управљања, вештачку интелигенцију, мехатронику и посебно биомедицинско инжењерство. Публиковао је око 80 радова у часописима са СЦИ листе, а његови цитатни индекси су h=23 у бази SCOPUS и h=24 у бази Google Scholar. Професор Жарко Ћојбашић тренутно ради као уговорени експерт Европске уније за области роботика, управљање, вештачка интелигенција и биомедицинско инжењерство.

Selected references – Selektovane reference

1. Ćojbasić Ž. (2019), Machine Learning for Personalized Medicine: Clinical Outcome Prediction and Diagnosis, 2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics (SACI), DOI: 10.1109/SACI46893.2019.9111519.
2. Hut, I., Jeftic, B., Matija, L., Cojbasic, Z., Koruga, D. (2019), Machine learning classification of cervical tissue liquid based cytology smear images by optomagnetic imaging spectroscopy, Tehnicki Vjesnik, 2019, 26(6), pp. 1694–1699. (M23 IF₂₀₂₀=0.786)
3. Lukić S., Ćojbasić Ž., Perić Z., Milošević Z., Spasić M., Pavlović V., Milojević A. (2012), Artificial neural networks based early clinical prediction of mortality after spontaneous intracerebral hemorrhage, Acta Neurologica Belgica,  112, Issue 4, Page 375-382, DOI: 10.1007/s13760-012-0093-2. (M23 IF₂₀₁₁=0.535)
4. Lukić S., Ćojbašić Ž. , Milošević Z. (2012), Comparation of artificial neural network and logistic regression models for predicting clinically relevant outcome, World Neurosurgery, DOI: 10.1016/j.wneu.2012.07.005.
5. Ćojbašić Ž., Brkić D. (2013), Very accurate explicit approximations for calculation of the Colebrook friction factor, International Journal of Mechanical Sciences, Volume 67, February 2013, Pages 10–13, DOI:10.1016/j.ijmecsci.2012.11.017.
6. Cojbasic Z., Petkovic D., Shamshirband S., Chong Wen T., Sudheer Ch., Jankovic P., Ducic N., Baralic J. (2015), Surface roughness prediction by extreme learning machineconstructed with abrasive water jet, Precision Engineering, Journal of the International Societies for Precision Engineering and Nanotechnology, 2015, http://dx.doi.org/10.1016/j.precisioneng.2015.06.013.
7. Ćojbašić, I., Mačukanović-Golubović, L., Vučić, M., Ćojbašić Z. (2019), Generic Imatinib in Chronic Myeloid Leukemia Treatment: Long-Term Follow-up, Clinical Lymphoma, Myeloma and Leukemia, 2019, 19(9), pp. e526–e531 (M22 IF₂₀₂₀=2.930).
8. Milojević, A., Linß, S., Ćojbašić, Z., Handroos, H. (2021), A novel simple, adaptive, and versatile soft-robotic compliant two-finger gripper with an inherently gentle touch, Journal of Mechanisms and Robotics, 2021, 13(1), 011015 (M22 IF₂₀₂₀=2.309)
9. Petković D., Ćojbašić Ž. (2012), Adaptive neuro-fuzzy estimation of autonomic nervous system parameters effect on heart rate variability, Neural Computing & Applications, 2012, Volume 21, Number 8, Pages 2065-2070, DOI: 10.1007/s00521-011-0629-z. 
10. Ćojbašić I, Vučić M, Tijanić I, Ćojbašić Ž (2022), Impact of quality of response on survival outcomes among multiple myeloma patients treated with novel agents – a retrospective analysis, Sao Paulo Med J. 2022; 140(2):222-8, https://doi.org/10.1590/1516-3180.2021.0174.R2.22062021.
11. Lukić, Ž. Ćojbašić, D. D. Markushev (2022), Trace gases analysis in pulsed photoacoustics based on swarm intelligence optimization, Optical and Quantum Electronics volume 54, Article number: 674 (2022) (M22), https://link.springer.com/article/10.1007/s11082-022-04059-y
12. Lj Djordjević, К., Galović, S.P., Ćojbašić, Ž.M. et al. (2022), Electronic characterization of plasma-thick n-type silicon using neural networks and photoacoustic response. Opt Quant Electron 54, 485, https://doi.org/10.1007/s11082-022-03808-3.
13. Dučić N., Manasijević S., Jovičić A., Ćojbašić Ž., Radiša R. (2022), Casting Process Improvement by the Application of Artificial Intelligence, Appl. Sci. 2022, 12, 3264. https://doi.org/10.3390/app12073264.
14. Stanković A., Petrović G., Marković D., Ćojbašić Ž. (2022), Solving Flexible Job Shop Scheduling Problem with Transportation Time Based on Neuro -Fuzzy Suggested Metaheuristics, Acta Polytechnica Hungarica 19, No. 4, 2022, DOI: 10.12700/APH.19.4.2022.4.11.
15. K Lj Djordjevic, M I Jordović-Pavlović, Ž М Ćojbašić, S P Galović, M N Popović, M V Nešić, D D Markushev (2022), Influence of data scaling and normalization on overall neural network performances in photoacoustics, Optical and Quantum Electronics, DOI: 10.21203/rs.3.rs-942309/v1.