T. Ganesan

869 total citations
49 papers, 448 citations indexed

About

T. Ganesan is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Biomedical Engineering. According to data from OpenAlex, T. Ganesan has authored 49 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 11 papers in Computational Theory and Mathematics and 8 papers in Biomedical Engineering. Recurrent topics in T. Ganesan's work include Advanced Multi-Objective Optimization Algorithms (11 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Cosmology and Gravitation Theories (7 papers). T. Ganesan is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (11 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Cosmology and Gravitation Theories (7 papers). T. Ganesan collaborates with scholars based in Malaysia, Canada and Pakistan. T. Ganesan's co-authors include Irraivan Elamvazuthi, Pandian Vasant, Ku Zilati Ku Shaari, Lila Iznita Izhar, Igor Litvinchev, S. Parasuraman, M.K.A. Ahamed Khan, Z. Yousaf, M. Z. Bhatti and Bander Almutairi and has published in prestigious journals such as Applied Energy, Applied Soft Computing and Neural Computing and Applications.

In The Last Decade

T. Ganesan

44 papers receiving 428 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
T. Ganesan Malaysia 14 108 104 83 74 57 49 448
Sew Sun Tiang Malaysia 11 157 1.5× 72 0.7× 117 1.4× 78 1.1× 57 1.0× 47 430
Kunal Gupta India 8 140 1.3× 68 0.7× 127 1.5× 40 0.5× 41 0.7× 33 597
Luka Eciolaza Spain 10 172 1.6× 227 2.2× 77 0.9× 44 0.6× 101 1.8× 35 561
Najdan Vuković Serbia 11 240 2.2× 116 1.1× 74 0.9× 50 0.7× 128 2.2× 15 539
Thanh-Hung Nguyen Vietnam 13 113 1.0× 54 0.5× 51 0.6× 93 1.3× 46 0.8× 52 499
Erkan Tanyıldızı Türkiye 9 233 2.2× 77 0.7× 78 0.9× 59 0.8× 28 0.5× 34 536
Ling He China 11 152 1.4× 171 1.6× 58 0.7× 40 0.5× 30 0.5× 28 537
Jose M. Lanza-Gutiérrez Spain 12 108 1.0× 43 0.4× 102 1.2× 50 0.7× 61 1.1× 41 551
Marko Mitić Serbia 11 176 1.6× 117 1.1× 58 0.7× 48 0.6× 133 2.3× 14 515
Yongliang Yuan China 10 200 1.9× 76 0.7× 124 1.5× 105 1.4× 28 0.5× 23 486

Countries citing papers authored by T. Ganesan

Since Specialization
Citations

This map shows the geographic impact of T. Ganesan'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 T. Ganesan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Ganesan more than expected).

Fields of papers citing papers by T. Ganesan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Ganesan

This figure shows the co-authorship network connecting the top 25 collaborators of T. Ganesan. A scholar is included among the top collaborators of T. Ganesan 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 T. Ganesan. T. Ganesan 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.
Yousaf, Z., et al.. (2025). Role of electromagnetic fields and Gauss–Bonnet gravity in the development of inhomogeneities in collapsing fluids. Physics of the Dark Universe. 49. 102058–102058.
2.
Yousaf, Z., S. Khan, Bander Almutairi, T. Ganesan, & M. Z. Bhatti. (2025). Gravitationally decoupled fuzzy black holes inspired by Einasto density profile. Chinese Journal of Physics. 97. 210–222. 2 indexed citations
3.
Almutairi, Bander, et al.. (2025). Role of polytropic equation of state through structure scalars in the complex self-gravitating systems. Physics of the Dark Universe. 48. 101835–101835. 2 indexed citations
4.
Yousaf, Z., T. Ganesan, Bander Almutairi, M. Z. Bhatti, & S. Khan. (2024). Effect of Einasto spike on the gravitationally decoupled self-gravitating dark matter halos. Physica Scripta. 99(12). 125302–125302. 5 indexed citations
5.
Ganesan, T.. (2024). Relativistic Formulation in Dual Minkowski Spacetime. Symmetry. 16(4). 482–482.
6.
Yousaf, Z., Bander Almutairi, Muhammad Rizwan, T. Ganesan, & M. Z. Bhatti. (2024). Modeling less complex fuzzy dark matter cylindrical wormholes. International Journal of Modern Physics D. 34(2). 7 indexed citations
7.
Ganesan, T. & Irraivan Elamvazuthi. (2023). Entanglement Distillation Optimization Using Fuzzy Relations for Quantum State Tomography. Algorithms. 16(7). 313–313. 1 indexed citations
8.
Ganesan, T., Pandian Vasant, & Irraivan Elamvazuthi. (2016). Multiobjective optimization using particle swarm optimization with non-Gaussian random generators. Intelligent Decision Technologies. 10(2). 93–103. 2 indexed citations
9.
Ganesan, T., Pandian Vasant, & Irraivan Elamvazuthi. (2016). Advances in Metaheuristics: Applications in Engineering Systems. 7 indexed citations
10.
Ganesan, T. & Irraivan Elamvazuthi. (2016). A multi-objective approach for resilience-based plant design optimization. Quality Engineering. 29(4). 656–671. 6 indexed citations
11.
Elamvazuthi, Irraivan, et al.. (2014). Performance Enhancement of PID Tuning of DC Servomotor using Metaheuristic Algorithm. International Journal of Scientific Engineering and Technology. 3(7). 951–954. 2 indexed citations
12.
Ganesan, T., Irraivan Elamvazuthi, Ku Zilati Ku Shaari, & Pandian Vasant. (2013). An Algorithmic Framework for Multiobjective Optimization. The Scientific World JOURNAL. 2013(1). 859701–859701. 6 indexed citations
13.
Vasant, Pandian, T. Ganesan, & Irraivan Elamvazuthi. (2012). Hybrid Tabu Search Hopfield Recurrent ANN Fuzzy Technique to the Production Planning Problems. 2(1). 47–65. 1 indexed citations
14.
Ganesan, T., Irraivan Elamvazuthi, Ku Zilati Ku Shaari, & Pandian Vasant. (2012). Swarm intelligence and gravitational search algorithm for multi-objective optimization of synthesis gas production. Applied Energy. 103. 368–374. 68 indexed citations
15.
Mariappan, Muralindran, et al.. (2011). Fuzzy Logic Based Navigation Safety System for a Remote Controlled Orthopaedic Robot (OTOROB). UMS Institutional Repository (Universiti Malaysia Sabah). 1 indexed citations
16.
Vasant, Pandian, et al.. (2011). Interactive fuzzy programming for the production planning: the case of textile firm. International Review on Modelling and Simulations (IREMOS). 4(2). 961. 9 indexed citations
17.
Elamvazuthi, Irraivan, T. Ganesan, & Pandian Vasant. (2011). A comparative study of HNN and Hybrid HNN-PSO techniques in the optimization of distributed generation (DG) power systems. 195–200. 6 indexed citations
18.
Ganesan, T., Pandian Vasant, & Irraivan Elamvazuthi. (2011). Optimization of nonlinear geological structure mapping using hybrid neuro-genetic techniques. Mathematical and Computer Modelling. 54(11-12). 2913–2922. 27 indexed citations
19.
Ganesan, T., Irraivan Elamvazuthi, & Pandian Vasant. (2011). Evolutionary normal-boundary intersection (ENBI) method for multi-objective optimization of green sand mould system. 4487. 86–91. 6 indexed citations
20.

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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