Nikhil R. Pal

22.5k total citations · 5 hit papers
266 papers, 15.5k citations indexed

About

Nikhil R. Pal is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Nikhil R. Pal has authored 266 papers receiving a total of 15.5k indexed citations (citations by other indexed papers that have themselves been cited), including 156 papers in Artificial Intelligence, 76 papers in Computer Vision and Pattern Recognition and 43 papers in Computational Theory and Mathematics. Recurrent topics in Nikhil R. Pal's work include Neural Networks and Applications (87 papers), Fuzzy Logic and Control Systems (59 papers) and Face and Expression Recognition (35 papers). Nikhil R. Pal is often cited by papers focused on Neural Networks and Applications (87 papers), Fuzzy Logic and Control Systems (59 papers) and Face and Expression Recognition (35 papers). Nikhil R. Pal collaborates with scholars based in India, United States and China. Nikhil R. Pal's co-authors include James C. Bezdek, Sankar K. Pal, Rajani K. Mudi, Kuhu Pal, James M. Keller, Raghu Krisnapuram, James F. Keller, Dinabandhu Bhandari, Eric Chen-Kuo Tsao and Jayanta Kumar Das and has published in prestigious journals such as Bioinformatics, PLoS ONE and Remote Sensing of Environment.

In The Last Decade

Nikhil R. Pal

250 papers receiving 14.5k citations

Hit Papers

A review on image segmentation techniques 1993 2026 2004 2015 1993 1995 2005 1999 1998 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nikhil R. Pal India 55 7.5k 5.3k 1.7k 1.7k 1.7k 266 15.5k
James M. Keller United States 47 5.6k 0.7× 4.8k 0.9× 698 0.4× 1.3k 0.8× 997 0.6× 464 13.1k
Sankar K. Pal India 58 6.9k 0.9× 5.9k 1.1× 932 0.5× 2.2k 1.3× 1.6k 0.9× 332 16.5k
John Langford United States 37 7.2k 1.0× 6.0k 1.1× 884 0.5× 977 0.6× 1.2k 0.7× 115 15.1k
Alexander J. Smola United States 42 11.8k 1.6× 8.8k 1.7× 2.5k 1.4× 1.6k 0.9× 998 0.6× 100 25.2k
Christopher J. C. Burges United States 27 9.5k 1.3× 7.4k 1.4× 2.2k 1.3× 1.4k 0.8× 950 0.6× 43 23.5k
Olivier Chapelle United States 45 7.7k 1.0× 5.5k 1.0× 1.0k 0.6× 888 0.5× 1.0k 0.6× 89 14.1k
Jieping Ye United States 87 7.9k 1.1× 8.7k 1.6× 1.5k 0.9× 1.6k 0.9× 462 0.3× 439 25.3k
Peter L. Bartlett United States 42 7.4k 1.0× 3.3k 0.6× 1.3k 0.8× 344 0.2× 1.1k 0.6× 200 12.3k
Joydeep Ghosh United States 48 6.9k 0.9× 3.7k 0.7× 547 0.3× 1.9k 1.1× 556 0.3× 308 14.9k
Ludmila I. Kuncheva United Kingdom 45 7.5k 1.0× 3.6k 0.7× 608 0.4× 761 0.4× 563 0.3× 128 12.3k

Countries citing papers authored by Nikhil R. Pal

Since Specialization
Citations

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

Fields of papers citing papers by Nikhil R. Pal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nikhil R. Pal

This figure shows the co-authorship network connecting the top 25 collaborators of Nikhil R. Pal. A scholar is included among the top collaborators of Nikhil R. Pal 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 Nikhil R. Pal. Nikhil R. Pal 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.
Chang, Qin, et al.. (2025). Multihead Takagi–Sugeno–Kang Fuzzy System. IEEE Transactions on Fuzzy Systems. 33(8). 2561–2573.
2.
Sheng, Yin, et al.. (2025). Sampled-Data-Based Event-Triggered Output-Feedback Consensus for Uncertain Heterogeneous High-Order Multiagent Systems. IEEE Transactions on Systems Man and Cybernetics Systems. 55(9). 5897–5911.
3.
Wang, Jian, Gai‐Ge Wang, Yong Zhang, et al.. (2025). A two-mode offspring generation selection mechanism with co-evolution for sparse large-scale multiobjective optimization. Information Sciences. 718. 122337–122337. 1 indexed citations
4.
Wang, Jian, et al.. (2024). Bi-Level Spectral Feature Selection. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 6597–6611. 4 indexed citations
5.
Wang, Jian, et al.. (2024). Universal Approximation Abilities of a Modular Differentiable Neural Network. IEEE Transactions on Neural Networks and Learning Systems. 36(3). 5586–5600. 5 indexed citations
6.
Chang, Qin, et al.. (2024). Takagi–Sugeno–Kang Fuzzy Systems for High-Dimensional Multilabel Classification. IEEE Transactions on Fuzzy Systems. 32(6). 3790–3804. 7 indexed citations
7.
Chang, Qin, et al.. (2024). Adaptive Nonstationary Fuzzy Neural Network. Knowledge-Based Systems. 288. 111398–111398. 10 indexed citations
8.
Wang, Jian, et al.. (2023). High-Dimensional Fuzzy Inference Systems. IEEE Transactions on Systems Man and Cybernetics Systems. 54(1). 507–519. 15 indexed citations
9.
Chang, Qin, et al.. (2022). An Adaptive Neuro-Fuzzy System With Integrated Feature Selection and Rule Extraction for High-Dimensional Classification Problems. IEEE Transactions on Fuzzy Systems. 31(7). 2167–2181. 63 indexed citations
10.
Lin, Chin‐Teng, Yuting Liu, Chun‐Hsiang Chuang, et al.. (2019). An Adaptive Subspace Self-Organizing Map (ASSOM) Imbalanced Learning and Its Applications in EEG.. arXiv (Cornell University). 1 indexed citations
11.
Pal, Nikhil R., et al.. (2019). Deep and Structure-Preserving Autoencoders for Clustering Data With Missing Information. IEEE Transactions on Emerging Topics in Computational Intelligence. 5(4). 639–650. 16 indexed citations
12.
Zhang, Hao, Nikhil R. Pal, Yin Sheng, & Zhigang Zeng. (2018). Distributed Adaptive Tracking Synchronization for Coupled Reaction–Diffusion Neural Network. IEEE Transactions on Neural Networks and Learning Systems. 30(5). 1462–1475. 50 indexed citations
13.
Chung, I‐Fang, Yi-Cheng Chen, & Nikhil R. Pal. (2017). Feature Selection With Controlled Redundancy in a Fuzzy Rule Based Framework. IEEE Transactions on Fuzzy Systems. 26(2). 734–748. 40 indexed citations
14.
Pal, Nikhil R., et al.. (2016). Finding Synergy Networks From Gene Expression Data: A Fuzzy-Rule-Based Approach. IEEE Transactions on Fuzzy Systems. 24(6). 1488–1499. 3 indexed citations
15.
Paul, Samrat, et al.. (2009). NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM. Journal of Machine Learning Research. 10(21). 591–622. 15 indexed citations
16.
Pal, Nikhil R. & Lokesh Jain. (2005). Advanced techniques in data mining and knowledge discovery. Springer eBooks. 2 indexed citations
17.
Pal, Nikhil R., et al.. (2003). Connectionist models for approximate solutions of non-linear equations in one variable. Neural, Parallel & Scientific Computations archive. 11(3). 185–206. 1 indexed citations
18.
Pal, Kuhu & Nikhil R. Pal. (1998). Learning of rule importance for fuzzy controllers to deal with inconsistent rules and for rule elimination. Control and Cybernetics. 27(4). 521–543. 1 indexed citations
19.
Pal, Nikhil R., et al.. (1997). Neural Networks for Dimensionality Reduction.. International Conference on Neural Information Processing. 221–224. 6 indexed citations
20.
Bezdek, James C., Richard J. Hathaway, & Nikhil R. Pal. (1995). Norm-induced shell-prototypes (NISP) clustering. Neural, Parallel & Scientific Computations archive. 3(4). 431–449. 11 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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