G. Ugrasen

562 total citations
31 papers, 421 citations indexed

About

G. Ugrasen is a scholar working on Mechanical Engineering, Electrical and Electronic Engineering and Biomedical Engineering. According to data from OpenAlex, G. Ugrasen has authored 31 papers receiving a total of 421 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Mechanical Engineering, 25 papers in Electrical and Electronic Engineering and 15 papers in Biomedical Engineering. Recurrent topics in G. Ugrasen's work include Advanced Machining and Optimization Techniques (25 papers), Advanced machining processes and optimization (22 papers) and Advanced Surface Polishing Techniques (14 papers). G. Ugrasen is often cited by papers focused on Advanced Machining and Optimization Techniques (25 papers), Advanced machining processes and optimization (22 papers) and Advanced Surface Polishing Techniques (14 papers). G. Ugrasen collaborates with scholars based in India and United States. G. Ugrasen's co-authors include H.V. Ravindra, R. Keshavamurthy, G. Vijaya Prakash, Kamal Kumar, Rajesh Sagar, B. Singaravel, G.S. Pradeep Kumar and P. Gomathi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Materials Today Proceedings and Materials Technology.

In The Last Decade

G. Ugrasen

29 papers receiving 379 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G. Ugrasen India 12 392 233 145 66 52 31 421
B. Ravi Sankar India 13 431 1.1× 124 0.5× 222 1.5× 59 0.9× 125 2.4× 43 531
Thella Babu Rao India 12 496 1.3× 198 0.8× 129 0.9× 67 1.0× 87 1.7× 43 546
Ahmet Taşkesen Türkiye 6 349 0.9× 207 0.9× 138 1.0× 23 0.3× 33 0.6× 12 362
Basanta Kumar Nanda India 13 282 0.7× 184 0.8× 194 1.3× 18 0.3× 32 0.6× 34 374
Lianjia Xin China 10 314 0.8× 143 0.6× 230 1.6× 79 1.2× 54 1.0× 15 390
P. Jeyapandiarajan India 10 282 0.7× 122 0.5× 67 0.5× 21 0.3× 71 1.4× 37 323
Engin Nas Türkiye 12 414 1.1× 262 1.1× 173 1.2× 15 0.2× 130 2.5× 30 490
Mulugundam Siva Surya India 16 435 1.1× 76 0.3× 173 1.2× 173 2.6× 111 2.1× 32 571
Zhichao Niu United Kingdom 8 331 0.8× 118 0.5× 166 1.1× 10 0.2× 59 1.1× 21 386
Mudimallana Goud India 12 424 1.1× 391 1.7× 334 2.3× 21 0.3× 25 0.5× 29 480

Countries citing papers authored by G. Ugrasen

Since Specialization
Citations

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

Fields of papers citing papers by G. Ugrasen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Ugrasen

This figure shows the co-authorship network connecting the top 25 collaborators of G. Ugrasen. A scholar is included among the top collaborators of G. Ugrasen 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 G. Ugrasen. G. Ugrasen 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.
Keshavamurthy, R., et al.. (2024). Tensile characteristics of metal filled 3D printed PLA based polymer composites. Interactions. 245(1). 4 indexed citations
2.
3.
Singaravel, B., et al.. (2022). Prediction of cutting forces using MRA, GMDH and ANN techniques in micro end milling of titanium alloy. Materials Today Proceedings. 72. 1943–1949. 8 indexed citations
4.
Keshavamurthy, R., et al.. (2020). Prediction of machining characteristics of Abrasive Water Jet Machined Al7075-TiB2 In-situ composite. Materials Today Proceedings. 24. 851–858. 3 indexed citations
5.
Ravindra, H.V., et al.. (2019). Estimation and Comparison of Electrode Wear and Ae Parameters of Titanium Material in Wire Electric Discharge Machining Using ANN. Applied Mechanics and Materials. 895. 144–151. 4 indexed citations
6.
Ugrasen, G., et al.. (2018). Optimization of Process Parameters for SS304 in Wire Electrical Discharge Machining using Taguchi’s Technique. Materials Today Proceedings. 5(1). 2877–2883. 12 indexed citations
7.
Ugrasen, G., et al.. (2018). Estimation of Machining Performances using MRA and GMDH in Wire EDM of Al2024 based Hybrid MMC. Materials Today Proceedings. 5(1). 3084–3092. 7 indexed citations
8.
Ugrasen, G., et al.. (2018). Optimization of Process Parameters for Al6061-Al7075 alloys in Friction Stir Welding using Taguchi’s Technique. Materials Today Proceedings. 5(1). 3027–3035. 25 indexed citations
9.
Ravindra, H.V., et al.. (2018). Estimation and Comparison of Welding Performances in P- GMAW using MRA and ANN for SS 304L Material. IOP Conference Series Materials Science and Engineering. 376. 12119–12119. 3 indexed citations
10.
Ravindra, H.V., et al.. (2017). Estimation of Machining Performances in WEDM of Aluminium based Metal Matrix Composite Material using ANN. Materials Today Proceedings. 4(9). 10035–10038. 20 indexed citations
11.
Ravindra, H.V., et al.. (2015). Optimization of Process Parameters in Drilling of Epoxy Si3N4 Composite Material. Materials Today Proceedings. 2(4-5). 2852–2861. 26 indexed citations
12.
Ugrasen, G., et al.. (2015). Hardness and Wear Characteristics of Hybrid Aluminium Metal Matrix Composites Produced by Stir Casting Technique. Materials Today Proceedings. 2(4-5). 2878–2885. 86 indexed citations
13.
Ugrasen, G., et al.. (2015). Optimization of Process Parameters in Wire EDM of HCHCr Material Using Taguchi's Technique. Materials Today Proceedings. 2(4-5). 2443–2452. 22 indexed citations
14.
Ravindra, H.V., et al.. (2014). Optimization of Process Parameters in Drilling Al-Si3N4 Metal Matrix Composites Material Using Taguchi Technique. Procedia Materials Science. 5. 2207–2214. 10 indexed citations
15.
Ugrasen, G., H.V. Ravindra, G. Vijaya Prakash, & R. Keshavamurthy. (2014). Process Optimization and Estimation of Machining Performances Using Artificial Neural Network in Wire EDM. Procedia Materials Science. 6. 1752–1760. 50 indexed citations
16.
17.
Ravindra, H.V., et al.. (2014). Estimation of Circularity, Cylindricity and Surface Roughness in Drilling Al-Si 3 N 4 Metal Matrix Composites Using Artificial Neural Network. Procedia Materials Science. 6. 1780–1787. 14 indexed citations
18.
Ugrasen, G., H.V. Ravindra, G. Vijaya Prakash, & R. Keshavamurthy. (2014). Estimation of Machining Performances Using MRA, GMDH and Artificial Neural Network in Wire EDM of EN-31. Procedia Materials Science. 6. 1788–1797. 18 indexed citations
19.
Keshavamurthy, R., et al.. (2014). Experimental Investigations on Wire EDM of Al7075-TiB<sub>2</sub> <i>In Situ</i> Metal Matrix Composite. Applied Mechanics and Materials. 592-594. 321–325. 8 indexed citations
20.
Keshavamurthy, R., et al.. (2014). Estimation of Tribological Behavior of Al2024-TiB<sub>2</sub> <i>In Situ</i> Composite Using GMDH and ANN. Applied Mechanics and Materials. 592-594. 1310–1314. 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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