Anindya Halder

658 total citations
38 papers, 397 citations indexed

About

Anindya Halder is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Anindya Halder has authored 38 papers receiving a total of 397 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 11 papers in Molecular Biology. Recurrent topics in Anindya Halder's work include Gene expression and cancer classification (8 papers), Rough Sets and Fuzzy Logic (6 papers) and Face and Expression Recognition (5 papers). Anindya Halder is often cited by papers focused on Gene expression and cancer classification (8 papers), Rough Sets and Fuzzy Logic (6 papers) and Face and Expression Recognition (5 papers). Anindya Halder collaborates with scholars based in India. Anindya Halder's co-authors include Ashish Ghosh, Susmita Ghosh, Utpal Biswas, Moumita Roy, Rajat Kumar Pal, Goutam Saha, Bimala P. Baruah and Goutam Saha and has published in prestigious journals such as Scientific Reports, Pattern Recognition and Information Sciences.

In The Last Decade

Anindya Halder

32 papers receiving 383 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anindya Halder India 12 198 85 52 49 42 38 397
Tamazouzt Ait Saadi Algeria 5 212 1.1× 68 0.8× 93 1.8× 71 1.4× 26 0.6× 6 379
Hao Dong China 13 211 1.1× 140 1.6× 52 1.0× 92 1.9× 43 1.0× 27 585
Seyyid Ahmed Medjahed Algeria 7 175 0.9× 97 1.1× 58 1.1× 113 2.3× 25 0.6× 16 421
Robert E. Banfield United States 8 323 1.6× 104 1.2× 34 0.7× 18 0.4× 33 0.8× 12 514
Mohammed M. Abdelsamea Egypt 17 425 2.1× 233 2.7× 35 0.7× 66 1.3× 13 0.3× 35 829
Loay E. George Iraq 12 165 0.8× 384 4.5× 23 0.4× 70 1.4× 21 0.5× 159 731
Mark Junjie Li China 11 301 1.5× 148 1.7× 108 2.1× 27 0.6× 47 1.1× 26 596
Athena Stassopoulou Cyprus 11 166 0.8× 24 0.3× 18 0.3× 26 0.5× 18 0.4× 17 433
Wei Zhong United States 9 170 0.9× 37 0.4× 94 1.8× 8 0.2× 20 0.5× 34 414
Kishor K. Bhoyar India 9 118 0.6× 144 1.7× 14 0.3× 17 0.3× 9 0.2× 34 380

Countries citing papers authored by Anindya Halder

Since Specialization
Citations

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

Fields of papers citing papers by Anindya Halder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anindya Halder

This figure shows the co-authorship network connecting the top 25 collaborators of Anindya Halder. A scholar is included among the top collaborators of Anindya Halder 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 Anindya Halder. Anindya Halder 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.
Halder, Anindya, et al.. (2025). RateNet: a deep neural framework for inferring ratings from textual features. Knowledge and Information Systems. 67(12). 11633–11673.
2.
Baruah, Bimala P., et al.. (2025). Protein sequence-based classification of Alzheimer’s disease using deep learning and attention mechanism. Iran Journal of Computer Science. 8(4). 2605–2633.
3.
Halder, Anindya, et al.. (2025). A novel deep sequential learning architecture for drug drug interaction prediction using DDINet. Scientific Reports. 15(1). 9337–9337. 1 indexed citations
4.
Halder, Anindya, et al.. (2024). AttentivECGRU: GRU based autoencoder with attention mechanism and automated fuzzy thresholding for ECG arrhythmia detection. Applied Soft Computing. 167. 112337–112337. 2 indexed citations
5.
Halder, Anindya, et al.. (2024). Application Of Density-Based Clustering Approaches For Stock Market Analysis. Applied Artificial Intelligence. 38(1).
6.
Halder, Anindya, et al.. (2024). Detection of Dense Built-Up Area in Low-Resolution Satellite Images Using Deep Learning and DBSCAN Approaches. International Journal of Pattern Recognition and Artificial Intelligence. 38(4).
7.
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9.
Halder, Anindya, et al.. (2024). Semi-supervised fuzzy-rough extreme learning machine for classification of cancer from microRNA. International Journal of Machine Learning and Cybernetics. 15(10). 4537–4548. 4 indexed citations
10.
Roy, Moumita, et al.. (2023). ECG-NET: A deep LSTM autoencoder for detecting anomalous ECG. Engineering Applications of Artificial Intelligence. 124. 106484–106484. 31 indexed citations
11.
Halder, Anindya, et al.. (2022). Computational analysis of gene expression data using bidirectional long short-term memory for disease diagnosis. Innovations in Systems and Software Engineering. 21(1). 93–107. 3 indexed citations
12.
Halder, Anindya, et al.. (2021). R-HEFS: Rough set based heterogeneous ensemble feature selection method for medical data classification. Artificial Intelligence in Medicine. 114. 102049–102049. 40 indexed citations
13.
Halder, Anindya, et al.. (2021). Partially Supervised Kernel Induced Rough Fuzzy Clustering for Brain Tissue Segmentation. Pattern Recognition and Image Analysis. 31(1). 91–102. 4 indexed citations
14.
Halder, Anindya, et al.. (2019). R-Ensembler: A greedy rough set based ensemble attribute selection algorithm with kNN imputation for classification of medical data. Computer Methods and Programs in Biomedicine. 184. 105122–105122. 55 indexed citations
15.
Halder, Anindya, et al.. (2019). Brain tissue segmentation using improved kernelized rough-fuzzy C-means with spatio-contextual information from MRI. Magnetic Resonance Imaging. 62. 129–151. 13 indexed citations
16.
Halder, Anindya, et al.. (2019). Active learning using rough fuzzy classifier for cancer prediction from microarray gene expression data. Journal of Biomedical Informatics. 92. 103136–103136. 24 indexed citations
17.
Halder, Anindya, et al.. (2019). Robust brain magnetic resonance image segmentation using modified rough-fuzzy C-means with spatial constraints. Applied Soft Computing. 85. 105758–105758. 15 indexed citations
18.
Halder, Anindya, et al.. (2014). Semi-supervised fuzzy K-NN for cancer classification from microarray gene expression data. 1–5. 11 indexed citations
19.
Halder, Anindya, Ashish Ghosh, & Susmita Ghosh. (2011). Supervised and unsupervised landuse map generation from remotely sensed images using ant based systems. Applied Soft Computing. 11(8). 5770–5781. 41 indexed citations
20.
Halder, Anindya, Ashish Ghosh, & Susmita Ghosh. (2009). Aggregation Pheromone Density Based Pattern Classification. Fundamenta Informaticae. 92(4). 345–362. 16 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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