Miloš Madić

1.4k total citations
98 papers, 1.1k citations indexed

About

Miloš Madić is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Miloš Madić has authored 98 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Mechanical Engineering, 38 papers in Industrial and Manufacturing Engineering and 31 papers in Electrical and Electronic Engineering. Recurrent topics in Miloš Madić's work include Advanced machining processes and optimization (43 papers), Manufacturing Process and Optimization (35 papers) and Advanced Machining and Optimization Techniques (29 papers). Miloš Madić is often cited by papers focused on Advanced machining processes and optimization (43 papers), Manufacturing Process and Optimization (35 papers) and Advanced Machining and Optimization Techniques (29 papers). Miloš Madić collaborates with scholars based in Serbia, Romania and Germany. Miloš Madić's co-authors include Miroslav Radovanović, Dušan Petković, Jurgita Antuchevičienė, Marin Gostimirović, Dragan Marinković, Žarko Ćojbašić, Dragan Rodić, Milenko Sekulić, Goran Radenković and Valentina Gečevska and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Expert Systems with Applications.

In The Last Decade

Miloš Madić

89 papers receiving 1.0k 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 Madić Serbia 20 502 333 239 222 180 98 1.1k
Miroslav Radovanović Serbia 17 412 0.8× 246 0.7× 163 0.7× 90 0.4× 141 0.8× 71 775
S. Kumanan India 26 848 1.7× 396 1.2× 598 2.5× 315 1.4× 75 0.4× 90 1.9k
V. Selladurai India 19 390 0.8× 76 0.2× 218 0.9× 109 0.5× 132 0.7× 86 1.1k
Roberto Gabbrielli Italy 20 526 1.0× 108 0.3× 119 0.5× 149 0.7× 49 0.3× 72 1.3k
A R Mileham United Kingdom 23 404 0.8× 229 0.7× 836 3.5× 116 0.5× 92 0.5× 101 1.6k
James R. Burns United States 12 397 0.8× 252 0.8× 65 0.3× 193 0.9× 125 0.7× 54 942
Goran Šimunović Croatia 17 343 0.7× 250 0.8× 178 0.7× 133 0.6× 51 0.3× 64 749
Jiang Lin China 7 774 1.5× 665 2.0× 249 1.0× 151 0.7× 55 0.3× 22 1.3k
Ali Abdulshahed Libya 12 321 0.6× 83 0.2× 72 0.3× 229 1.0× 119 0.7× 21 827
Saeed Talebi Iran 16 220 0.4× 75 0.2× 125 0.5× 151 0.7× 103 0.6× 99 1.1k

Countries citing papers authored by Miloš Madić

Since Specialization
Citations

This map shows the geographic impact of Miloš Madić'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 Madić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miloš Madić more than expected).

Fields of papers citing papers by Miloš Madić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miloš Madić. 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 Madić. The network helps show where Miloš Madić may publish in the future.

Co-authorship network of co-authors of Miloš Madić

This figure shows the co-authorship network connecting the top 25 collaborators of Miloš Madić. A scholar is included among the top collaborators of Miloš Madić 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 Madić. Miloš Madić 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.
Banić, Milan, et al.. (2025). The Use of Earth Observation Data for Railway Infrastructure Monitoring—A Review. Infrastructures. 10(3). 66–66. 1 indexed citations
2.
Madić, Miloš, et al.. (2025). Analysis of cut radii dimensional accuracy in CO 2 fusion laser cutting. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 240(4). 504–513.
3.
Madić, Miloš, et al.. (2024). Fiber Laser Cutting Technology: Pilot Case Study in Mild Steel Cutting. 1(1). 1–9. 3 indexed citations
4.
Madić, Miloš, et al.. (2024). Traditional and Integrated MCDM Approaches for Assessment and Ranking of Laser Cutting Conditions. 1(1). 250–257. 6 indexed citations
5.
Gupta, Kapil, et al.. (2023). AN INVESTIGATION ON MEAN ROUGHNESS DEPTH AND MATERIAL EROSION SPEED DURING MANUFACTURING OF STAINLESS-STEEL MINIATURE RATCHET GEARS BY WIRE-EDM. Facta Universitatis Series Mechanical Engineering. 21(2). 239–239. 6 indexed citations
6.
Zolfani, Sarfaraz Hashemkhani, et al.. (2023). Comparison of Aggregation Operators in the Group Decision-Making Process: A Real Case Study of Location Selection Problem. Sustainability. 15(10). 8229–8229. 6 indexed citations
7.
Madić, Miloš, et al.. (2023). Empirical Modeling Methods of Turning Process: A Review. 1(2). 74–81.
9.
Madić, Miloš, Miroslav Radovanović, & Marko Kovačević. (2017). AN OPTIMIZATION APPROACH FOR PRODUCTION TIME MINIMIZATION IN LONGITUDINAL TURNING. 20(2). 39–44.
10.
Madić, Miloš, Miroslav Radovanović, & Dušan Petković. (2015). NON-CONVENTIONAL MACHINING PROCESSES SELECTION USING MULTI-OBJECTIVE OPTIMIZATION ON THE BASIS OF RATIO ANALYSIS METHOD. SHILAP Revista de lepidopterología. 10 indexed citations
11.
Madić, Miloš, et al.. (2015). Multi-Objective Tire Design Optimization by Artificial Neural Networks. International Conference on Information Society. 111–114. 1 indexed citations
12.
Petković, Dušan, et al.. (2015). Decision Support System for Selection of the Most Suitable Biomedical Material. International Conference on Information Society. 27–31. 4 indexed citations
13.
Madić, Miloš. (2015). Multi-objective optimization of cut quality characteristic in CO2 laser cutting stainless steel. Tehnicki vjesnik - Technical Gazette. 22(4). 885–892. 9 indexed citations
14.
Madić, Miloš, et al.. (2014). Optimization of CO 2 Laser Cutting Process using Taguchi and Dual Response Surface Methodology. Tribology in Industry. 36(3). 236–243. 10 indexed citations
15.
Madić, Miloš, et al.. (2013). Modeling and Simulated Annealing Optimization of Surface Roughness in CO2 Laser Nitrogen Cutting of Stainless Steel. SHILAP Revista de lepidopterología. 3 indexed citations
16.
Madić, Miloš, et al.. (2012). Cutting Parameters Optimization for Surface Roughness in Turning Operation of Polyethylene (PE) Using Taguchi Method. SHILAP Revista de lepidopterología. 20 indexed citations
17.
Madić, Miloš & Miroslav Radovanović. (2012). AN ARTIFICIAL INTELLIGENCE APPROACH FOR THE PREDICTION OF SURFACE ROUGHNESS IN CO2 LASER CUTTING. SHILAP Revista de lepidopterología. 5 indexed citations
18.
Madić, Miloš, Goran Radenković, & Miroslav Radovanović. (2012). Evaluation of ANN-BP and ANN-GA Models Performance in Predicting Mechanical Properties and Machinability of Cast Copper Alloys. University of Zagreb University Computing Centre (SRCE). 54(2). 169–174. 1 indexed citations
19.
Madić, Miloš & Miroslav Radovanović. (2011). Optimal Selection of ANN Training and Architectural Parameters Using Taguchi Method: A Case Study. FME Transaction. 39(2). 79–86. 35 indexed citations
20.
Madić, Miloš, et al.. (2010). Assessing the sensitivity of the artificial neural network to experimental noise: A case study. SHILAP Revista de lepidopterología. 4 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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