A. Chandrasekar

1.4k total citations
108 papers, 886 citations indexed

About

A. Chandrasekar is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Plant Science. According to data from OpenAlex, A. Chandrasekar has authored 108 papers receiving a total of 886 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Electrical and Electronic Engineering, 25 papers in Computer Networks and Communications and 22 papers in Plant Science. Recurrent topics in A. Chandrasekar's work include Banana Cultivation and Research (17 papers), Energy Efficient Wireless Sensor Networks (12 papers) and Microwave Engineering and Waveguides (11 papers). A. Chandrasekar is often cited by papers focused on Banana Cultivation and Research (17 papers), Energy Efficient Wireless Sensor Networks (12 papers) and Microwave Engineering and Waveguides (11 papers). A. Chandrasekar collaborates with scholars based in India, United States and Romania. A. Chandrasekar's co-authors include P. Ramesh, S. Radhika, S. Backiyarani, S. Uma, Felix Albu, M. S. Saraswathi, M. Muthusamy, R. Thangavelu, V. Arunachalam and S. Hemavathi and has published in prestigious journals such as Gene, Frontiers in Plant Science and Planta.

In The Last Decade

A. Chandrasekar

97 papers receiving 824 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. Chandrasekar India 17 254 236 158 152 97 108 886
Aly El Gamal United States 12 213 0.8× 242 1.0× 112 0.7× 152 1.0× 46 0.5× 45 768
Jianxin Guo China 14 153 0.6× 116 0.5× 188 1.2× 109 0.7× 22 0.2× 81 774
Ece Olcay Güneş Türkiye 16 266 1.0× 457 1.9× 35 0.2× 49 0.3× 116 1.2× 68 910
Shengjie Zhao China 20 222 0.9× 354 1.5× 110 0.7× 80 0.5× 19 0.2× 75 1.1k
Lijun He China 15 142 0.6× 175 0.7× 44 0.3× 206 1.4× 36 0.4× 53 756
Muhammad Tufail Pakistan 16 177 0.7× 476 2.0× 163 1.0× 68 0.4× 19 0.2× 45 894
Jingzhi Hu China 13 523 2.1× 47 0.2× 423 2.7× 323 2.1× 20 0.2× 37 913
Taewoon Kim South Korea 12 259 1.0× 26 0.1× 69 0.4× 305 2.0× 23 0.2× 49 581
Stojan Denic United States 11 405 1.6× 241 1.0× 43 0.3× 126 0.8× 9 0.1× 34 922
Hailin Xiao China 20 914 3.6× 61 0.3× 409 2.6× 447 2.9× 16 0.2× 96 1.2k

Countries citing papers authored by A. Chandrasekar

Since Specialization
Citations

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

Fields of papers citing papers by A. Chandrasekar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Chandrasekar

This figure shows the co-authorship network connecting the top 25 collaborators of A. Chandrasekar. A scholar is included among the top collaborators of A. Chandrasekar 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 A. Chandrasekar. A. Chandrasekar 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.
Chandrasekar, A., et al.. (2024). Fatigue and Sluggishness Detection Using Machine Learning: A Haar Algorithmic Approach. 1–5. 1 indexed citations
2.
Chandrasekar, A., et al.. (2023). A multi-fusion integrated end-to-end deep kernel CNN based channel estimation for hybrid range UM-MIMO 6G communication systems. Applied Acoustics. 210. 109427–109427. 5 indexed citations
3.
Chandrasekar, A., et al.. (2023). Hybrid Deep Learning Approach for 6G MIMO Channel Estimation and Interference Alignment HetNet Environments. Traitement du signal. 40(5). 1951–1930.
4.
Chandrasekar, A., et al.. (2023). Optimal deep generative adversarial network and convolutional neural network for rice leaf disease prediction. The Visual Computer. 40(2). 919–936. 26 indexed citations
5.
Chandrasekar, A., et al.. (2023). SOSO: Symbiotic Organisms Search Optimization based Faster RCNN for Secure DataStorage in Cloud. IETE Journal of Research. 70(2). 1196–1208. 3 indexed citations
6.
Radhika, S., et al.. (2023). An Efficient Hybrid Ensemble SVM for Optimal Channel and Power Allocation Using Chaotic Quantum Bat Optimization. IETE Journal of Research. 69(10). 7041–7050. 1 indexed citations
7.
8.
Radhika, S., Felix Albu, & A. Chandrasekar. (2022). Robust Exponential Hyperbolic Sine Adaptive Filter for Impulsive Noise Environments. IEEE Transactions on Circuits & Systems II Express Briefs. 69(12). 5149–5153. 24 indexed citations
9.
Saraswathi, M. S., R. Thangavelu, S. Uma, et al.. (2022). Development of fusarium wilt resistant mutants of Musa spp. cv.Rasthali (AAB, Silk subgroup) and comparative proteomic analysis along with its wild type. Planta. 255(4). 80–80. 2 indexed citations
10.
Radhika, S., Felix Albu, & A. Chandrasekar. (2021). Proportionate Maximum Versoria Criterion-Based Adaptive Algorithm for Sparse System Identification. IEEE Transactions on Circuits & Systems II Express Briefs. 69(3). 1902–1906. 21 indexed citations
11.
Venkatesan, K., A. Chandrasekar, P. Ramesh, & C.R. Selvakumar. (2021). Theoretical investigation for optimization of FWM effects for 1Tb/s ultra-band DWDM system. Optoelectronics and Advanced Materials Rapid Communications. 15. 148–156. 2 indexed citations
12.
Chandrasekar, A., et al.. (2020). Genetic spider monkey‐based routing protocol to increase the lifetime of the network and energy management in WSN. International Journal of Communication Systems. 33(14). 16 indexed citations
13.
Chandrasekar, A., et al.. (2020). CAD System for Lung Cancer and its Stages Detection using Image processing Techniques. International Journal of Innovative Technology and Exploring Engineering. 9(4). 1612–1615. 2 indexed citations
14.
Chandrasekar, A., et al.. (2019). An Efficient Multi Level Intrusion Detection System for Mobile Ad-Hoc Network Using Clustering Technique. International Journal of Engineering and Advanced Technology. 8(6). 1977–1985. 9 indexed citations
15.
Chandrasekar, A., et al.. (2019). NBN Gene Analysis and it’s Impact on Breast Cancer. Journal of Medical Systems. 43(8). 270–270. 6 indexed citations
16.
Chandrasekar, A., et al.. (2019). Autonomous Data hiding in an Encrypted Image using KM-DH Algorithm. International Journal of Innovative Technology and Exploring Engineering. 9(2). 4950–4952. 1 indexed citations
17.
Muthusamy, M., S. Uma, S. Backiyarani, M. S. Saraswathi, & A. Chandrasekar. (2016). Transcriptomic Changes of Drought-Tolerant and Sensitive Banana Cultivars Exposed to Drought Stress. Frontiers in Plant Science. 7. 1609–1609. 67 indexed citations
18.
Chandrasekar, A., et al.. (2013). An Incremental Clustering Technique to Privacy Preservation Over Incremental Cloud Data. International Review on Computers and Software (IRECOS). 8(11). 2746–2754. 5 indexed citations
19.
Chandrasekar, A., et al.. (2013). Fast and Efficient Opinion Mining Technique for Online Reviews Using Ranking and Classification Algorithms. International Review on Computers and Software (IRECOS). 8(7). 1587–1595. 1 indexed citations
20.
Rajesh, M. K., et al.. (2009). Mining of expressed sequence tag libraries of cacao for microsatellite markers using five computational tools. Journal of Genetics. 88(2). 217–225. 7 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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