M. Sridharan

632 total citations
55 papers, 449 citations indexed

About

M. Sridharan is a scholar working on Artificial Intelligence, Renewable Energy, Sustainability and the Environment and Mechanical Engineering. According to data from OpenAlex, M. Sridharan has authored 55 papers receiving a total of 449 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 19 papers in Renewable Energy, Sustainability and the Environment and 9 papers in Mechanical Engineering. Recurrent topics in M. Sridharan's work include Solar Radiation and Photovoltaics (17 papers), Solar Thermal and Photovoltaic Systems (17 papers) and Photovoltaic System Optimization Techniques (15 papers). M. Sridharan is often cited by papers focused on Solar Radiation and Photovoltaics (17 papers), Solar Thermal and Photovoltaic Systems (17 papers) and Photovoltaic System Optimization Techniques (15 papers). M. Sridharan collaborates with scholars based in India, France and Iraq. M. Sridharan's co-authors include Soumya Roy, S. Sathyanarayanan, G. Jayaprakash, M. Chandrasekar, M. Arulmozhi, R. Manjula Devi, S. Suresh, M. Muthuraman, S. Aravind Raj and K. R. Parthasarathy and has published in prestigious journals such as Journal of Applied Physics, Electronics Letters and Process Safety and Environmental Protection.

In The Last Decade

M. Sridharan

53 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
M. Sridharan India 13 172 149 101 85 76 55 449
Arslan Habib China 6 144 0.8× 108 0.7× 45 0.4× 149 1.8× 41 0.5× 11 322
Emmanouil D. Fylladitakis Greece 11 102 0.6× 79 0.5× 31 0.3× 215 2.5× 34 0.4× 28 436
Jiaqi Qu China 6 128 0.7× 166 1.1× 74 0.7× 220 2.6× 27 0.4× 17 350
Arturo Pacheco-Vega United States 10 36 0.2× 72 0.5× 380 3.8× 53 0.6× 93 1.2× 50 661
Wolfgang Gawlik Austria 14 58 0.3× 12 0.1× 41 0.4× 480 5.6× 70 0.9× 57 640
Konrad Świrski Poland 9 77 0.4× 22 0.1× 46 0.5× 201 2.4× 55 0.7× 34 356
Saad A. Mohamed Abdelwahab Egypt 14 129 0.8× 61 0.4× 28 0.3× 364 4.3× 13 0.2× 46 477
Surbhi Agrawal India 9 266 1.5× 171 1.1× 85 0.8× 47 0.6× 24 0.3× 26 466
Yijun Chen China 16 230 1.3× 171 1.1× 42 0.4× 488 5.7× 29 0.4× 35 726

Countries citing papers authored by M. Sridharan

Since Specialization
Citations

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

Fields of papers citing papers by M. Sridharan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Sridharan

This figure shows the co-authorship network connecting the top 25 collaborators of M. Sridharan. A scholar is included among the top collaborators of M. Sridharan 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 M. Sridharan. M. Sridharan 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.
Muthuraman, M., et al.. (2024). Combining Graph Theory and Machine Learning for Network-Based Medical Image Analysis. 1–5. 3 indexed citations
2.
Sridharan, M., et al.. (2023). Employing ensemble machine learning techniques for predicting the thermohydraulic performance of double pipe heat exchanger with and without turbulators. Thermal Science and Engineering Progress. 47. 102337–102337. 18 indexed citations
3.
Sridharan, M., et al.. (2023). An adaptive neuro-fuzzy approach to predict the thermal efficiency of differently configured solar flat plate water collector systems. Environment Development and Sustainability. 26(3). 7079–7103. 5 indexed citations
4.
Muralikannan, R., et al.. (2023). AA4032-TiC-h-BN-related composites: a machine learning model-based experimental study with performance prediction. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 46(1). 3 indexed citations
5.
6.
Sridharan, M.. (2023). Performance Augmentation Study on a Solar Flat Plate Water Collector System with Modified Absorber Flow Design and its Performance Prediction Using the XGBoost Algorithm: A Machine Learning Approach. Iranian Journal of Science and Technology Transactions of Mechanical Engineering. 48(1). 133–144. 11 indexed citations
7.
Sridharan, M.. (2019). Application of Generalized Regression Neural Network in Predicting the Performance of Natural Convection Solar Dryer. Journal of Solar Energy Engineering. 142(3). 22 indexed citations
8.
Sridharan, M., et al.. (2018). Prediction of Solar Photovoltaic/Thermal Collector Power Output Using Fuzzy Logic. Journal of Solar Energy Engineering. 140(6). 24 indexed citations
9.
Manikandan, M., et al.. (2017). Performance Analysis And Experimental Investigation On Exhaust Gas Heat Recovery For IC Engines Using Shell And Tube Heat Exchanger. International Journal of Engineering and Applied Sciences (IJEAS). 4(7). 257415. 3 indexed citations
10.
Sridharan, M., et al.. (2014). Some Properties of Bipolar Fuzzy Cosets of a Bipolar Fuzzy and Bipolar Anti Fuzzy HX Subgroup. IOSR Journal of Mathematics. 9(6). 128–137. 1 indexed citations
11.
Sridharan, M., et al.. (2014). Performance Enhancement Study on SingleBasin Double Slope Solar Still Using Flat PlateCollector. International Journal of Innovative Research in Science Engineering and Technology. 3(3). 7 indexed citations
12.
Sridharan, M., et al.. (2014). Experimental Investigation on Series SolarFlat Plate Collectors with Variable Mass FlowRates. International Journal of Innovative Research in Science Engineering and Technology. 2014(3). 2 indexed citations
13.
Sridharan, M., et al.. (2014). Performance Improving Methods for SeriesSolar Flat Plate Collectors and Introduction ofNew Verification Tool. International Journal of Innovative Research in Science Engineering and Technology. 3(3). 1 indexed citations
14.
Sridharan, M., et al.. (2014). Steady State Analysis on Efficiency Improving Methods for Series Flat Plate Solar Water Heaters. Applied Mechanics and Materials. 592-594. 1784–1788. 4 indexed citations
15.
Sridharan, M. & Raja Selvaraj. (2009). Multi dimensional scaling of geomagnetic Sq (H) variations. 2 indexed citations
16.
Sridharan, M., et al.. (2005). Fuzzy clustering analysis to study geomagnetic coastal effects. Annales Geophysicae. 23(4). 1157–1163. 3 indexed citations
17.
18.
Sridharan, M., et al.. (1980). Effect of mobile space-charge on the small-signal admittance of DDR silicon IMPATTs at high current densities. Solid-State Electronics. 23(9). 1001–1003. 13 indexed citations
19.
Sridharan, M. & K. R. Parthasarathy. (1972). Isographs and oriented isographs. Journal of Combinatorial Theory Series B. 13(2). 99–111. 4 indexed citations
20.
Sridharan, M.. (1970). Self-complementary and self-converse oriented graphs. Indagationes Mathematicae (Proceedings). 73. 441–447. 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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