Jayadeva

3.7k total citations · 1 hit paper
75 papers, 2.6k citations indexed

About

Jayadeva is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Jayadeva has authored 75 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 23 papers in Computer Vision and Pattern Recognition and 9 papers in Signal Processing. Recurrent topics in Jayadeva's work include Face and Expression Recognition (19 papers), Neural Networks and Applications (17 papers) and Machine Learning and ELM (10 papers). Jayadeva is often cited by papers focused on Face and Expression Recognition (19 papers), Neural Networks and Applications (17 papers) and Machine Learning and ELM (10 papers). Jayadeva collaborates with scholars based in India, United States and Australia. Jayadeva's co-authors include Suresh Chandra, Reshma Rastogi, Dinesh Kumar, Ganesh R. Naik, N. M. Anoop Krishnan, Sumit Soman, Debarka Sengupta, R. Chattopadhyay, Anirban Guha and Mohd Zaki and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Jayadeva

70 papers receiving 2.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Twin Support Vector Machines for Pattern Classification

2007 1.4k citations Jayadeva, Suresh Chandra et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jayadeva India	20	1.2k	1.2k	513	218	205	75	2.6k
Suresh Chandra India	23	1.4k 1.1×	1.4k 1.2×	794 1.5×	112 0.5×	81 0.4×	79	2.7k
S. Lecœuche France	20	1.5k 1.2×	855 0.7×	871 1.7×	163 0.7×	210 1.0×	73	4.1k
Tom Dietterich United States	11	2.1k 1.7×	890 0.8×	288 0.6×	184 0.8×	153 0.7×	20	3.3k
David B. Rosen United States	11	2.1k 1.7×	731 0.6×	429 0.8×	187 0.9×	184 0.9×	20	3.3k
Pavel Pudil Czechia	15	1.5k 1.2×	1.3k 1.1×	173 0.3×	417 1.9×	265 1.3×	63	3.5k
Fanzhang Li China	23	906 0.7×	1.1k 1.0×	207 0.4×	156 0.7×	109 0.5×	139	2.3k
Takio Kurita Japan	24	642 0.5×	1.3k 1.1×	198 0.4×	165 0.8×	279 1.4×	204	2.6k
Mingbo Zhao China	28	811 0.7×	1.3k 1.1×	550 1.1×	63 0.3×	100 0.5×	123	2.6k
Chi‐Man Vong Macao	35	1.7k 1.4×	1.0k 0.9×	1.0k 2.0×	122 0.6×	349 1.7×	178	4.3k
Marius Kloft Germany	25	1.7k 1.4×	998 0.8×	255 0.5×	164 0.8×	168 0.8×	86	3.0k

Countries citing papers authored by Jayadeva

Since Specialization

Citations

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

Fields of papers citing papers by Jayadeva

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jayadeva

This figure shows the co-authorship network connecting the top 25 collaborators of Jayadeva. A scholar is included among the top collaborators of Jayadeva 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 Jayadeva. Jayadeva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Kumar, Sandeep, et al.. (2024). A Unified Optimization-Based Framework for Certifiably Robust and Fair Graph Neural Networks. IEEE Transactions on Signal Processing. 73. 83–98.

Jayadeva, et al.. (2024). No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 10775–10783. 13 indexed citations

Zaki, Mohd, Jayadeva, & N. M. Anoop Krishnan. (2024). Interpretable machine learning for understanding compositional and testing condition effects on refractive index, density, dielectric constant, and loss tangent of inorganic melts and glasses. Frontiers in Materials. 11. 3 indexed citations

Zaki, Mohd, Jayadeva, Mausam Mausam, & N. M. Anoop Krishnan. (2023). MaScQA: investigating materials science knowledge of large language models. Digital Discovery. 3(2). 313–327. 26 indexed citations

Rockstroh, Anja, Melanie Lehman, Apoorva Gupta, et al.. (2022). Gene expression based inference of cancer drug sensitivity. Nature Communications. 13(1). 5680–5680. 70 indexed citations

Ahuja, Gaurav, et al.. (2022). A new deep learning technique reveals the exclusive functional contributions of individual cancer mutations. Journal of Biological Chemistry. 298(8). 102177–102177. 5 indexed citations

Pant, Himanshu, Sumit Soman, Jayadeva, & Amit Bhaya. (2020). Neurodynamical classifiers with low model complexity. Neural Networks. 132. 405–415. 2 indexed citations

Thakral, Deepshi, Himanshu Pant, Pramod Kumar Verma, et al.. (2020). Molecular signature comprising 11 platelet-genes enables accurate blood-based diagnosis of NSCLC. BMC Genomics. 21(1). 744–744. 15 indexed citations

Jayadeva, et al.. (2018). Discovery of rare cells from voluminous single cell expression data. Nature Communications. 9(1). 4719–4719. 83 indexed citations

10.

Batra, Sanjit Singh, et al.. (2017). Sparse short-term time series forecasting models via minimum model complexity. Neurocomputing. 243. 1–11. 7 indexed citations

11.

Kumar, U. K. Arun, Sumit Soman, & Jayadeva. (2016). Benchmarking NLopt and state-of-the-art algorithms for continuous global optimization via IACO R. arXiv (Cornell University). 27. 116–131. 4 indexed citations

12.

Jayadeva, Reshma Rastogi, & Suresh Chandra. (2016). Twin Support Vector Machines. Studies in computational intelligence. 19 indexed citations

13.

Ikonomidou, Vasiliki N., Jayadeva, Robert W. Newcomb, & Mona Zaghloul. (2013). Biomedical sensor properties of flexible PolyVinyliDene flouride. 1–2. 2 indexed citations

14.

Naik, Ganesh R., Dinesh Kumar, & Jayadeva. (2010). Hybrid independent component analysis and twin support vector machine learning scheme for subtle gesture recognition. Biomedizinische Technik/Biomedical Engineering. 55(5). 301–307. 9 indexed citations

15.

Ahuja, Puneet, et al.. (2010). Reduced twin support vector regression. Neurocomputing. 74(9). 1474–1477. 30 indexed citations

16.

Naik, Ganesh R., Dinesh Kumar, & Jayadeva. (2009). Twin SVM for Gesture Classification Using the Surface Electromyogram. IEEE Transactions on Information Technology in Biomedicine. 14(2). 301–308. 112 indexed citations

17.

Deb, Alok Kanti, et al.. (2007). SVM-Based Tree-Type Neural Networks as a Critic in Adaptive Critic Designs for Control. IEEE Transactions on Neural Networks. 18(4). 1016–1030. 25 indexed citations

18.

Jayadeva, et al.. (2007). Twin Support Vector Machines for Pattern Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 29(5). 905–910. 1371 indexed citations breakdown →

19.

Jayadeva, Reshma Rastogi, & Suresh Chandra. (2004). Fast and robust learning through fuzzy linear proximal support vector machines. Neurocomputing. 61. 401–411. 39 indexed citations

20.

Chattopadhyay, R., Anirban Guha, & Jayadeva. (2003). Performance of neural networks for predicting yarn properties using principal component analysis. Journal of Applied Polymer Science. 91(3). 1746–1751. 18 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.

Explore authors with similar magnitude of impact