Miloš Ivanović

775 total citations
45 papers, 557 citations indexed

About

Miloš Ivanović is a scholar working on Biomedical Engineering, Cardiology and Cardiovascular Medicine and Computational Mechanics. According to data from OpenAlex, Miloš Ivanović has authored 45 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Biomedical Engineering, 7 papers in Cardiology and Cardiovascular Medicine and 7 papers in Computational Mechanics. Recurrent topics in Miloš Ivanović's work include Cardiomyopathy and Myosin Studies (6 papers), Model Reduction and Neural Networks (4 papers) and Cardiovascular Function and Risk Factors (3 papers). Miloš Ivanović is often cited by papers focused on Cardiomyopathy and Myosin Studies (6 papers), Model Reduction and Neural Networks (4 papers) and Cardiovascular Function and Risk Factors (3 papers). Miloš Ivanović collaborates with scholars based in Serbia, United States and Hong Kong. Miloš Ivanović's co-authors include Boban Stojanović, Suhas V. Patankar, E. M. Sparrow, Dejan Divac, Nikola Milivojević, Svetislav Savović, Nenad Filipović, Miloš Kojić, İvan Gutman and Boris Furtula and has published in prestigious journals such as Biophysical Journal, European Journal of Operational Research and Journal of Hydrology.

In The Last Decade

Miloš Ivanović

42 papers receiving 525 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Miloš Ivanović Serbia 13 100 83 78 53 50 45 557
Guan China 14 34 0.3× 36 0.4× 124 1.6× 83 1.6× 121 2.4× 212 769
Tim Brereton Germany 8 54 0.5× 30 0.4× 58 0.7× 37 0.7× 16 0.3× 16 623
Guoliang Zhang China 15 198 2.0× 87 1.0× 18 0.2× 23 0.4× 34 0.7× 50 611
Andrew E. Slaughter United States 13 46 0.5× 119 1.4× 191 2.4× 51 1.0× 21 0.4× 31 980
Hua Li China 14 19 0.2× 103 1.2× 55 0.7× 36 0.7× 16 0.3× 87 1.0k
Soumya Sahoo India 14 52 0.5× 28 0.3× 76 1.0× 71 1.3× 52 1.0× 92 790
Xiaohong Li China 15 56 0.6× 27 0.3× 162 2.1× 38 0.7× 37 0.7× 31 815
Pei Chen China 15 57 0.6× 50 0.6× 163 2.1× 57 1.1× 19 0.4× 77 647
Shuangqing Chen China 15 89 0.9× 21 0.3× 93 1.2× 18 0.3× 34 0.7× 36 793
Weifeng Wang China 13 75 0.8× 44 0.5× 53 0.7× 74 1.4× 19 0.4× 98 934

Countries citing papers authored by Miloš Ivanović

Since Specialization
Citations

This map shows the geographic impact of Miloš Ivanović's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Miloš Ivanović with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miloš Ivanović more than expected).

Fields of papers citing papers by Miloš Ivanović

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miloš Ivanović. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Miloš Ivanović. The network helps show where Miloš Ivanović may publish in the future.

Co-authorship network of co-authors of Miloš Ivanović

This figure shows the co-authorship network connecting the top 25 collaborators of Miloš Ivanović. A scholar is included among the top collaborators of Miloš Ivanović based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Miloš Ivanović. Miloš Ivanović is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Živić, Fatima, et al.. (2025). Materials informatics: A review of AI and machine learning tools, platforms, data repositories, and applications to architectured porous materials. Materials Today Communications. 48. 113525–113525. 3 indexed citations
2.
Savović, Svetislav, Miloš Ivanović, Branko Drljača, & Ana Simović. (2024). Numerical Solution of the Sine–Gordon Equation by Novel Physics-Informed Neural Networks and Two Different Finite Difference Methods. Axioms. 13(12). 872–872. 2 indexed citations
3.
Savović, Svetislav, Miloš Ivanović, & Rui Min. (2023). A Comparative Study of the Explicit Finite Difference Method and Physics-Informed Neural Networks for Solving the Burgers’ Equation. Axioms. 12(10). 982–982. 20 indexed citations
4.
Lampert, Thomas, et al.. (2023). Learning domain invariant representations of heterogeneous image data. Machine Learning. 112(10). 3659–3684. 2 indexed citations
5.
Ivanović, Miloš, et al.. (2023). OVERVIEW OF PHYSICS-INFORMED NEURAL NETWORKS APPLICATIONS. Contemporary Materials. 14(2). 1 indexed citations
6.
Stojanović, Boban, et al.. (2023). Identifying optimal architectures of physics-informed neural networks by evolutionary strategy. Applied Soft Computing. 146. 110646–110646. 16 indexed citations
7.
Barrasa‐Fano, Jorge, Christian Hellmich, Stefan Scheiner, et al.. (2023). SGABU computational platform for multiscale modeling: Bridging the gap between education and research. Computer Methods and Programs in Biomedicine. 243. 107935–107935.
8.
Nikolić, Aleksandar, et al.. (2022). Smoothed particle hydrodynamics for blood flow analysis: development of particle lifecycle algorithm. Computational Particle Mechanics. 9(6). 1119–1135. 5 indexed citations
9.
Ivanović, Miloš, et al.. (2022). Huxley muscle model surrogates for high-speed multi-scale simulations of cardiac contraction. Computers in Biology and Medicine. 149. 105963–105963. 4 indexed citations
10.
Šušteršič, Tijana, et al.. (2022). Development of SGABU Platform for Multiscale Modeling. 18(1). 50–55. 1 indexed citations
11.
Filipović, Nenad, Igor Šaveljić, Tijana Šušteršič, et al.. (2022). <em>In Silico</em> Clinical Trials for Cardiovascular Disease. Journal of Visualized Experiments. 1 indexed citations
12.
Simić, Vladimir, Miljan Milošević, Miloš Ivanović, et al.. (2022). Integration of Surrogate Huxley Muscle Model into Finite Element Solver for Simulation of the Cardiac Cycle. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2022. 3943–3946. 1 indexed citations
13.
Ivanović, Miloš, et al.. (2019). Optimal threshold of the prostate health index in predicting aggressive prostate cancer using predefined cost–benefit ratios and prevalence. International Urology and Nephrology. 52(5). 893–901. 3 indexed citations
14.
Ivanović, Miloš, et al.. (2016). The Application of the Topic Modeling to Question Answer Retrieval. International Conference on Information Society. 241–246. 2 indexed citations
15.
Ivanović, Miloš, et al.. (2016). Market risk management in a post-Basel II regulatory environment. European Journal of Operational Research. 257(3). 1030–1044. 13 indexed citations
16.
Stojanović, Boban, et al.. (2016). Multi-modeling and multi-scale modeling as tools for solving complex real-world problems. 10(1). 34–49. 1 indexed citations
17.
Jakovljević, Mihajlo, et al.. (2013). Radiology Services Costs and Utilization Patterns Estimates in Southeastern Europe—A Retrospective Analysis from Serbia. Value in Health Regional Issues. 2(2). 218–225. 36 indexed citations
18.
Kojić, Nikola, Austin Huang, Euiheon Chung, et al.. (2010). A 3-D Model of Ligand Transport in a Deforming Extracellular Space. Biophysical Journal. 99(11). 3517–3525. 8 indexed citations
19.
Filipović, Nenad, Miloš Ivanović, Damjan Krstajić, & Miloš Kojić. (2010). Hemodynamic Flow Modeling Through an Abdominal Aorta Aneurysm Using Data Mining Tools. IEEE Transactions on Information Technology in Biomedicine. 15(2). 189–194. 19 indexed citations
20.
Ivanović, Miloš. (1978). Prediction of flow and heat transfer in internally finned tubes. PhDT. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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