Aruna Tiwari

3.1k total citations · 1 hit paper
117 papers, 2.0k citations indexed

About

Aruna Tiwari is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Aruna Tiwari has authored 117 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Artificial Intelligence, 40 papers in Computer Vision and Pattern Recognition and 20 papers in Molecular Biology. Recurrent topics in Aruna Tiwari's work include Face and Expression Recognition (25 papers), Evolutionary Algorithms and Applications (18 papers) and Neural Networks and Applications (17 papers). Aruna Tiwari is often cited by papers focused on Face and Expression Recognition (25 papers), Evolutionary Algorithms and Applications (18 papers) and Neural Networks and Applications (17 papers). Aruna Tiwari collaborates with scholars based in India, Singapore and Australia. Aruna Tiwari's co-authors include Neha Bharill, Arpit Bhardwaj, Om Prakash Patel, Mukesh Prasad, Amit Saxena, Weiping Ding, Chin‐Teng Lin, Akshansh Gupta, Meng Joo Er and M. Tanveer and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Aruna Tiwari

104 papers receiving 1.9k citations

Hit Papers

A review of clustering techniques and developments 2017 2026 2020 2023 2017 250 500 750
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.

  1. A review of clustering techniques and developments
    2017 850 citations Neha Bharill, Aruna Tiwari et al. profile →

Peers

Aruna Tiwari
Hsuan-Tien Lin Taiwan
Michael Gray United States
Ming Zong China
Samir Brahim Belhaouari Qatar
Kun Zhang United States
Maurizio Filippone United Kingdom
Monica Bianchini Italy
Afshin Rostamizadeh United States
Shaoning Pang New Zealand
Gavin Brown United Kingdom
Hsuan-Tien Lin Taiwan
Aruna Tiwari
Citations per year, relative to Aruna Tiwari Aruna Tiwari (= 1×) peers Hsuan-Tien Lin

Countries citing papers authored by Aruna Tiwari

Since Specialization
Citations

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

Fields of papers citing papers by Aruna Tiwari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aruna Tiwari

This figure shows the co-authorship network connecting the top 25 collaborators of Aruna Tiwari. A scholar is included among the top collaborators of Aruna Tiwari 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 Aruna Tiwari. Aruna Tiwari 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.
Tiwari, Aruna, et al.. (2025). Leveraging Memory Forensic Features for Explainable Obfuscated Malware Detection with Isolated Family Distinction Paradigm. Computers & Electrical Engineering. 123. 110107–110107. 1 indexed citations
2.
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Tiwari, Aruna, et al.. (2025). On construction of data preprocessing for real-life SoyLeaf dataset & disease identification using Deep Learning Models. Computational Biology and Chemistry. 117. 108417–108417.
4.
Saurav, Sumeet, et al.. (2024). Attention-guided generator with dual discriminator GAN for real-time video anomaly detection. Engineering Applications of Artificial Intelligence. 131. 107830–107830. 23 indexed citations
5.
Saurav, Sumeet, et al.. (2024). CVAD-GAN: Constrained video anomaly detection via generative adversarial network. Image and Vision Computing. 143. 104950–104950. 7 indexed citations
6.
Tripathi, Abhishek, et al.. (2024). Enhancing K-means Clustering Performance with a Two-Stage Hybrid Preprocessing Strategy. Arabian Journal for Science and Engineering. 50(19). 15453–15472.
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Tiwari, Aruna, et al.. (2023). STemGAN: spatio-temporal generative adversarial network for video anomaly detection. Applied Intelligence. 53(23). 28133–28152. 11 indexed citations
9.
Tiwari, Aruna, et al.. (2023). A novel apache spark-based 14-dimensional scalable feature extraction approach for the clustering of genomics data. The Journal of Supercomputing. 80(3). 3554–3588. 4 indexed citations
10.
Tiwari, Aruna, et al.. (2023). Feature subset selection using multimodal multiobjective differential evolution. Knowledge-Based Systems. 265. 110361–110361. 15 indexed citations
11.
Tiwari, Aruna, et al.. (2021). Soft Computing for Problem Solving. Advances in intelligent systems and computing. 2 indexed citations
12.
Tiwari, Aruna, et al.. (2021). Apache Spark based kernelized fuzzy clustering framework for single nucleotide polymorphism sequence analysis. Computational Biology and Chemistry. 92. 107454–107454. 21 indexed citations
13.
Gautam, Chandan, Aruna Tiwari, Bharat Richhariya, et al.. (2019). Minimum variance-embedded deep kernel regularized least squares method for one-class classification and its applications to biomedical data. Neural Networks. 123. 191–216. 24 indexed citations
14.
Bhardwaj, Harshit, Aditi Sakalle, Aruna Tiwari, Madhushi Verma, & Arpit Bhardwaj. (2018). Breast Cancer Diagnosis using Simultaneous Feature Selection and Classification: A Genetic Programming Approach. 2186–2192. 7 indexed citations
15.
Gautam, Chandan & Aruna Tiwari. (2018). Localized Multiple Kernel Support Vector Data Description. 1514–1521. 3 indexed citations
16.
Bhardwaj, Arpit, et al.. (2016). A genetically optimized neural network model for multi-class classification. Expert Systems with Applications. 60. 211–221. 24 indexed citations
17.
Bhardwaj, Arpit, et al.. (2015). A novel genetic programming approach for epileptic seizure detection. Computer Methods and Programs in Biomedicine. 124. 2–18. 50 indexed citations
18.
Bhardwaj, Arpit, et al.. (2014). A genetically optimized neural network for classification of breast cancer disease. 693–698. 9 indexed citations
19.
Purohit, Anuradha, Arpit Bhardwaj, Aruna Tiwari, & Narendra S. Chaudhari. (2011). Handling the Problem of Code Bloating to Enhance the Performance of Classifier Designed Using Genetic Programming.. Indian International Conference on Artificial Intelligence. 333–342. 2 indexed citations
20.
Purohit, Anuradha, et al.. (2009). Improved Genetic Programming Based Multiclass Classifier Using a New Crossover Operator.. Indian International Conference on Artificial Intelligence. 67(3). 924–932. 1 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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