D.S. Srinivasu

715 total citations
36 papers, 485 citations indexed

About

D.S. Srinivasu is a scholar working on Ecological Modeling, Biomedical Engineering and Mechanical Engineering. According to data from OpenAlex, D.S. Srinivasu has authored 36 papers receiving a total of 485 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Ecological Modeling, 17 papers in Biomedical Engineering and 13 papers in Mechanical Engineering. Recurrent topics in D.S. Srinivasu's work include Erosion and Abrasive Machining (21 papers), Advanced Surface Polishing Techniques (16 papers) and Particle Dynamics in Fluid Flows (9 papers). D.S. Srinivasu is often cited by papers focused on Erosion and Abrasive Machining (21 papers), Advanced Surface Polishing Techniques (16 papers) and Particle Dynamics in Fluid Flows (9 papers). D.S. Srinivasu collaborates with scholars based in India, United Kingdom and United States. D.S. Srinivasu's co-authors include Dragoş Axinte, N. Ramesh Babu, P.H. Shipway, J. Folkes, Paul Butler‐Smith, M.C. Kong, N. Venkaiah, J. Billingham, Rajesh Ravi and Swatantra Kumar and has published in prestigious journals such as International Journal of Machine Tools and Manufacture, Applied Soft Computing and CIRP Annals.

In The Last Decade

D.S. Srinivasu

31 papers receiving 453 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D.S. Srinivasu India 12 315 251 197 108 104 36 485
W.C.K. Wong Australia 7 269 0.9× 180 0.7× 155 0.8× 110 1.0× 98 0.9× 11 379
G.A. Harmain India 15 83 0.3× 32 0.1× 358 1.8× 50 0.5× 132 1.3× 79 680
Chiara Ravasio Italy 12 50 0.2× 243 1.0× 298 1.5× 30 0.3× 29 0.3× 33 406
Miroslav Halilovič Slovenia 15 31 0.1× 83 0.3× 384 1.9× 14 0.1× 78 0.8× 49 568
Yangjian Xu China 14 62 0.2× 26 0.1× 252 1.3× 12 0.1× 130 1.3× 46 607
Mohamadreza Afrasiabi Switzerland 16 12 0.0× 119 0.5× 344 1.7× 71 0.7× 44 0.4× 47 581
Lucjan Witek Poland 15 46 0.1× 18 0.1× 539 2.7× 34 0.3× 164 1.6× 39 751
Moon-Chul Yoon South Korea 7 23 0.1× 151 0.6× 323 1.6× 12 0.1× 55 0.5× 48 375
T.V.K. Gupta India 13 41 0.1× 101 0.4× 413 2.1× 8 0.1× 19 0.2× 36 451
Arif Malik United States 16 37 0.1× 51 0.2× 453 2.3× 15 0.1× 15 0.1× 52 602

Countries citing papers authored by D.S. Srinivasu

Since Specialization
Citations

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

Fields of papers citing papers by D.S. Srinivasu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D.S. Srinivasu. 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 D.S. Srinivasu. The network helps show where D.S. Srinivasu may publish in the future.

Co-authorship network of co-authors of D.S. Srinivasu

This figure shows the co-authorship network connecting the top 25 collaborators of D.S. Srinivasu. A scholar is included among the top collaborators of D.S. Srinivasu 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 D.S. Srinivasu. D.S. Srinivasu 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.
Srinivasu, D.S., et al.. (2025). A new approach for product reliability prediction by considering the production factory lifecycle information. Reliability Engineering & System Safety. 258. 110915–110915. 3 indexed citations
2.
Ravi, Rajesh & D.S. Srinivasu. (2024). An experimental investigation into the influence of water column height in submerged mode of abrasive waterjet trepanning on the hole quality. Journal of Manufacturing Processes. 117. 170–192. 4 indexed citations
3.
4.
Babu, N. Ramesh, et al.. (2024). Effect of laser beam incident angle on welding of Ti6Al4V with fiber lasers. Manufacturing Letters. 41. 469–474. 1 indexed citations
5.
Srinivasu, D.S., et al.. (2023). Integration of CFD simulated abrasive waterjet flow dynamics with the material removal model for kerf geometry prediction in overlapped erosion on Ti-6Al-4V alloy. Simulation Modelling Practice and Theory. 127. 102788–102788. 10 indexed citations
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Srinivasu, D.S., et al.. (2023). Modelling the cross-sectional profile of the kerf generated in overlapped pass erosion in abrasive waterjet milling of Al6061-T6 alloy. Journal of Manufacturing Processes. 102. 297–318. 11 indexed citations
9.
Kumar, Swatantra & D.S. Srinivasu. (2022). Optimal number of thermal hotspots selection on motorized milling spindle to predict its thermal deformation. Materials Today Proceedings. 62. 3376–3385. 10 indexed citations
10.
Ravi, Rajesh, D.S. Srinivasu, & P. K. Behera. (2021). Machining Thin-walled 2 1/2 D Structure in a Novel Aluminium Carbon Fiber Composite Material by the Micro-Abrasive Waterjets – an experimental investigation. Advances in Materials and Processing Technologies. 8(3). 2619–2636. 1 indexed citations
11.
Srinivasu, D.S., et al.. (2020). Sqoop usage in Hadoop Distributed File System and Observations to Handle Common Errors. International Journal of Recent Technology and Engineering (IJRTE). 9(4). 452–454.
12.
Srinivasu, D.S., et al.. (2019). Edge AI System for Pneumonia and Lung Cancer Detection. International Journal of Innovative Technology and Exploring Engineering. 8(9). 1908–1915. 6 indexed citations
13.
Srinivasu, D.S., et al.. (2019). Efficient CNN for Lung Cancer Detection. International Journal of Recent Technology and Engineering (IJRTE). 8(2). 3499–3503. 14 indexed citations
14.
Rao, G. Siva Nageswara, et al.. (2018). Efficient PIMRR Algorithm Based on Scheduling Measures for Improving Real Time Systems. International Journal of Engineering & Technology. 7(2.32). 275–275.
15.
Srinivasu, D.S., et al.. (2016). Cfd Analysis To Predict Heat Transfer Performance Of Louver Fin Radiator With Water/Eg & Al2o3 Nano Fluid. 4(2). 159–164. 2 indexed citations
16.
Srinivasu, D.S. & Dragoş Axinte. (2014). Mask-Less Pocket Milling of Composites by Abrasive Waterjets: An Experimental Investigation. Journal of Manufacturing Science and Engineering. 136(4). 35 indexed citations
17.
Srinivasu, D.S. & Dragoş Axinte. (2011). An analytical model for top width of jet footprint in abrasive waterjet milling: a case study on SiC ceramics. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 225(3). 319–335. 16 indexed citations
18.
Axinte, Dragoş, D.S. Srinivasu, M.C. Kong, & Paul Butler‐Smith. (2009). Abrasive waterjet cutting of polycrystalline diamond: A preliminary investigation. International Journal of Machine Tools and Manufacture. 49(10). 797–803. 68 indexed citations
19.
Srinivasu, D.S. & N. Ramesh Babu. (2007). An adaptive control strategy for the abrasive waterjet cutting process with the integration of vision-based monitoring and a neuro-genetic control strategy. The International Journal of Advanced Manufacturing Technology. 38(5-6). 514–523. 13 indexed citations
20.
Srinivasu, D.S. & N. Ramesh Babu. (2007). A neuro-genetic approach for selection of process parameters in abrasive waterjet cutting considering variation in diameter of focusing nozzle. Applied Soft Computing. 8(1). 809–819. 48 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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