Prof. dr Tomo Popović, vanredni profesor, doktor tehničkih nauka (Elektrotehnički fakultet, Univerzitet Crne Gore), magistar inženjerstva (Electrical and Computer Engineering, Texas A&M University, USA), diplomirani inženjer elektrotehnike (Fakultet tehničkih nauka, Univerzitet u Novom Sadu). Prof. Popović aktivno učestvuje u nastavi računarstva i informacionih sistema. Ima 25 godina međunarodnog iskustva u industrijskom i akademskom okruženju (Srbija, SAD, Crna Gora). Njegovi noviji projekti uključuju razvoj softvera i arhitekturu Internet stvari platforme za preciznu poljoprivredu i eko-monitoring (BIO-ICT, HERIC), rješenje na bazi Interneta stvari i mobilne aplikacije za zaštitu brenda i prevenciju falsifikata u vinskoj industriji (TagItWine, H2020) i Digitalnu transformaciju poljoprivrede i lanca snabdijevanja hranom (DIPOL, nacionalni). Ovi projekti su doveli do novih projektnih prijava koje su odobrene za realizaciju: H2020 DEMETER, Erasmus+ VIRAL, IPA ECOMON, i Centar izvrsnosti Food-HUB. Najnoviji projekti uključuju H2020 EuroCC, H2020 AIMHiGH u okviru FF4EuroHPC. Njegov naučnoistraživački rad je usmjeren na primijenjene računarske nauke, posebno u domenu inteligentnih sistema, Interneta stvari, nauke o podacima sa primjenama u energetici, biomedicini, poljoprivredi i industrijskim sistemima. Tomo Popović ima preko 100 radova objavljenih u naučnim časopisima ili konferencijama. On je viši član IEEE (Senior member) i član ACM-a i CIGRE.

Naučni radovi:

-Pavicevic, M. and Popovic, T., Forecasting Day-Ahead Electricity Metrics with Artificial Neural Networks, Sensors 22(3):1051, MDPI, 2022, http://dx.doi.org/10.3390/s22031051 

-Popovic, N. et al., TREND database: Retinal images of healthy young subjects visualized by a portable digital non-mydriatic fundus camera, PLoS ONE 16(7):e0254918, PLOS, 2021, http://dx.doi.org/10.1371/journal.pone.0254918 

-Popovic, T. et al., A novel solution for counterfeit prevention in the wine industry based on IoT, smart tags, and crowd-sourced information, Internet of Things 14C(2012):100375, Elsevier, 2021, http://dx.doi.org/10.1016/j.iot.2021.100375 

-Zecevic, Z. et al., An efficient phasor and frequency estimation algorithm for wide frequency range, Electric Power Systems research 180(2020), Elsevier, 2020, http://dx.doi.org/10.1016/j.epsr.2019.106124 

-Popovic, N. et al., Regional Patterns in Retinal Microvascular Network Geometry in Health and Disease, Scientific Reports 9(1):16340, Nature, 2019, https://www.nature.com/articles/s41598-019-52659-8 

-Popovic, N. et al., Fractal Characterization of Retinal Microvascular Network Morphology During Diabetic Retinopathy Progression, Microcirculation 26(4), Wiley, 2019, http://dx.doi.org/10.1111/micc.12531 

-Popovic, N. et al., Fractal dimension and lacunarity analysis of retinal microvascular morphology in hypertension and diabetes, Microvascular Research 118(2018), Elsevier, 2018, http://dx.doi.org/10.1016/j.mvr.2018.02.006 

-Popovic, N. et al., A Moodle-Based Blended Learning Solution for Physiology Education in Montenegro: A Case Study, AJP Advances in Physiology Education, 2018, http://dx.doi.org/10.1152/advan.00155.2017 

-Popovic, T. et al., Architecting an IoT-enabled platform for precision agriculture and ecological monitoring: A case study, Computers and Electronics in Agriculture 2017(140C), Elsevier, 2018, http://dx.doi.org/10.1016/j.compag.2017.06.008 

-Malbasa, V. et al., Voltage Stability Prediction Using Active Machine Learning, IEEE transactions on Smart Grid 8(6), IEEE, 2017, http://dx.doi.org/10.1109/TSG.2017.2693394 

-Popovic, T. et al., Implementation requirements for automated fault data analytics in power systems 25(4), Wiley, 2014, http://dx.doi.org/10.1002/etep.1872 

-Zecevic, Z. et al., Improved Frequency Estimation in Unbalanced Three-Phase Power System Using Coupled Orthogonal Constant Modulus Algorithm, IEEE Transactions on Power Delivery 32(4):1809-1816, 2016, http://dx.doi.org/10.1109/TPWRD.2016.2586106 

-Popovic, T. et al., Getting ISO 9001 Certified for Software Development Using Scrum and Open Source: A Case Study, Technical Gazette, 2015, http://dx.doi.org/10.17559/TV-20140704180948 

-Esmaeillian, A. et al., Transmission line relay mis-operation detection based on time-synchronized field data, Electric Power Systems research 125(2015):174-183, Elsevier, 2015, http://dx.doi.org/10.1016/j.epsr.2015.04.008 

-Popovic, T. et al., Implementation requirements for automated fault data analytics in power systems, International Transactions on Electrical Energy Systems 25(4):731-752, Wiley, 2014, http://dx.doi.org/10.1002/etep.1872 

-Popovic, T. et al., Smart Grid Data Analytics for Digital Protective Relay Event Recordings, Inofrmation Systems Frontiers 17(3):591-600, Springer, 2013, http://dx.doi.org/10.1007/s10796-013-9434-9 

-Popovic, T. and Keznovic, M., Measures of Value: Data Analytics for Automated Fault Analysis, IEEE Power and Energy Magazine 10(5):58-69, 2012, http://dx.doi.org/10.1109/MPE.2012.2205319