Ram Subbiah

5.1k total citations
210 papers, 2.9k citations indexed

About

Ram Subbiah is a scholar working on Mechanical Engineering, Mechanics of Materials and Materials Chemistry. According to data from OpenAlex, Ram Subbiah has authored 210 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 145 papers in Mechanical Engineering, 67 papers in Mechanics of Materials and 56 papers in Materials Chemistry. Recurrent topics in Ram Subbiah's work include Metal and Thin Film Mechanics (42 papers), Aluminum Alloys Composites Properties (40 papers) and Advanced Machining and Optimization Techniques (34 papers). Ram Subbiah is often cited by papers focused on Metal and Thin Film Mechanics (42 papers), Aluminum Alloys Composites Properties (40 papers) and Advanced Machining and Optimization Techniques (34 papers). Ram Subbiah collaborates with scholars based in India, Ethiopia and Nepal. Ram Subbiah's co-authors include P. Manoj Kumar, Asif Afzal, P.T. Saravanakumar, N. Sateesh, J. Saranya, S. Rajkumar, Moti Lal Rinawa, Rajasekaran Saminathan, Sahana Dinesh and S. Arunkumar and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sustainability and Colloids and Surfaces A Physicochemical and Engineering Aspects.

In The Last Decade

Ram Subbiah

191 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ram Subbiah India 31 1.8k 664 618 445 434 210 2.9k
V. Mohanavel India 34 2.2k 1.2× 711 1.1× 355 0.6× 462 1.0× 603 1.4× 242 3.9k
B. Stalin India 29 1.8k 1.0× 374 0.6× 340 0.6× 434 1.0× 392 0.9× 128 2.5k
Mohit Sharma India 26 1.1k 0.6× 808 1.2× 840 1.4× 620 1.4× 281 0.6× 83 2.5k
Senthil Kumaran Selvaraj India 37 2.7k 1.5× 855 1.3× 658 1.1× 391 0.9× 511 1.2× 258 4.6k
Seyed Saeid Rahimian Koloor Malaysia 29 894 0.5× 379 0.6× 781 1.3× 403 0.9× 428 1.0× 133 2.6k
Kiran Shahapurkar India 24 755 0.4× 334 0.5× 268 0.4× 426 1.0× 775 1.8× 102 2.1k
Hamid Khayyam Australia 34 1.7k 1.0× 933 1.4× 415 0.7× 691 1.6× 467 1.1× 86 4.0k
Md. Abdul Maleque Malaysia 34 2.4k 1.4× 497 0.7× 937 1.5× 1.1k 2.6× 1.1k 2.4× 191 3.8k
Abhinav Kumar India 22 691 0.4× 365 0.5× 222 0.4× 217 0.5× 392 0.9× 271 2.0k
Dipen Kumar Rajak India 23 1.7k 1.0× 718 1.1× 1.2k 1.9× 1.1k 2.4× 392 0.9× 73 3.5k

Countries citing papers authored by Ram Subbiah

Since Specialization
Citations

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

Fields of papers citing papers by Ram Subbiah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ram Subbiah

This figure shows the co-authorship network connecting the top 25 collaborators of Ram Subbiah. A scholar is included among the top collaborators of Ram Subbiah 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 Ram Subbiah. Ram Subbiah 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.
2.
Satishkumar, P., Barun Haldar, Nashmi H. Alrasheedi, et al.. (2025). Artificial neural network based prediction of specific wear rate in Al7475 composites reinforced with industrial wastes. Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science. 239(11). 4182–4193. 1 indexed citations
3.
Subbiah, Ram, et al.. (2024). Assessment of wear behavior on treated AISI 310 by liquid nitriding process. AIP conference proceedings. 3007. 100037–100037.
4.
Subbiah, Ram, et al.. (2023). Dry sliding wear Behaviour analysis on treatedAISI 431 stainless steel material by annealing and tempering process. Advances in Materials and Processing Technologies. 10(4). 2732–2740. 1 indexed citations
5.
Subbiah, Ram, et al.. (2023). Investigation of Wear Characteristics on Gas Nitrided AISI 304 Stainless Steel under Dry Sliding Conditions. SHILAP Revista de lepidopterología. 391. 1091–1091.
6.
Haldar, Barun, A. Pradeep, M. Naga Swapna Sri, et al.. (2023). Multi-objective optimization using Taguchi based grey relational analysis in friction stir welding for dissimilar aluminium alloy. International Journal on Interactive Design and Manufacturing (IJIDeM). 18(3). 1627–1644. 33 indexed citations
7.
Munimathan, Arunkumar, Ram Subbiah, P. Ganeshan, et al.. (2023). EXTRACTION, PERFORMANCE AND EMISSION CHARACTERIZATION OF DIESEL ENGINE USING WASTE LIPOLYTIC MICROORGANISM BIODIESEL. Global NEST Journal. 6 indexed citations
8.
Subbiah, Ram, et al.. (2023). Fabrication and properties valuation of Natural fiber and filler-based hybrid-polymer composites. SHILAP Revista de lepidopterología. 430. 1145–1145. 2 indexed citations
9.
10.
Saranya, J., et al.. (2022). Recent reviews on bio-waste materials for corrosion protection of metals. Corrosion Reviews. 40(4). 335–342. 2 indexed citations
11.
Logesh, K., et al.. (2022). Investigations of Nanoparticles (Al2O3‐SiO2) Addition on the Mechanical Properties of Blended Matrix Polymer Composite. Journal of Nanomaterials. 2022(1). 3 indexed citations
12.
Venkatraman, R., S. Raghuraman, P. Manoj Kumar, et al.. (2022). Processing of Aluminium-Silicon Alloy with Metal Carbide as Reinforcement through Powder-Based Additive Manufacturing: A Critical Study. Scanning. 2022. 1–14. 53 indexed citations
13.
Sivakumar, N., et al.. (2022). Wear Behavior and FESEM Analysis of LM 25 Alloy MMHCs Reinforced with FE3O4 and Gr by Utilizing Taguchi’s Technique. Journal of Nanomaterials. 2022(1). 5 indexed citations
14.
Manickavasagam, V.M., et al.. (2022). Mechanical and optimization studies of polyethylene/snail shell/ kenaf fiber hybrid bio composite. Materials Today Proceedings. 69. 1087–1095. 1 indexed citations
15.
Saranya, J., et al.. (2021). Quinoxaline derivatives as anticorrosion additives for metals. Corrosion Reviews. 39(2). 79–92. 13 indexed citations
16.
Natrayan, L., et al.. (2021). Evaluating the Mechanical and Tribological Properties of DLC Nanocoated Aluminium 5051 Using RF Sputtering. Journal of Nanomaterials. 2021. 1–7. 21 indexed citations
17.
Rao, Ch. Srinivasa, et al.. (2021). Formability of tailor welded blanks of aluminium alloy and steel – A review. Materials Today Proceedings. 46. 722–728. 7 indexed citations
18.
Sateesh, N., et al.. (2020). Effect of RF carbonitriding and improvement of mechanical properties on AISI 304 stainless steel – A review. Materials Today Proceedings. 27. 1655–1659. 7 indexed citations
19.
Saranya, J., et al.. (2020). Assessment of AISI 431Grade Stainless Steel properties by Vacuum Tempering Process. SHILAP Revista de lepidopterología. 184. 1022–1022. 20 indexed citations
20.
Ilangovan, R., et al.. (1990). Effect of spacing, nitrogen and phosphorus on certain growth parameters of senna (Cassia angustifolia Vahl.).. 38(1). 53–54. 3 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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