Apurva Narayan

776 total citations
59 papers, 482 citations indexed

About

Apurva Narayan is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Apurva Narayan has authored 59 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 8 papers in Molecular Biology and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Apurva Narayan's work include Anomaly Detection Techniques and Applications (12 papers), Adversarial Robustness in Machine Learning (7 papers) and Software Reliability and Analysis Research (7 papers). Apurva Narayan is often cited by papers focused on Anomaly Detection Techniques and Applications (12 papers), Adversarial Robustness in Machine Learning (7 papers) and Software Reliability and Analysis Research (7 papers). Apurva Narayan collaborates with scholars based in Canada, India and United States. Apurva Narayan's co-authors include K. Ponnambalam, Keith W. Hipel, Sebastian Fischmeister, Abbas S. Milani, Rudolf Seethaler, Bryn Crawford, Heinz Voggenreiter, Ushnik Mukherjee, Ali Elkamel and Azadeh Maroufmashat and has published in prestigious journals such as Scientific Reports, IEEE Access and Renewable Energy.

In The Last Decade

Apurva Narayan

47 papers receiving 467 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Apurva Narayan Canada 11 188 104 86 75 43 59 482
Xiaoli Xu China 10 152 0.8× 89 0.9× 187 2.2× 29 0.4× 53 1.2× 84 579
Huijun Liang China 11 392 2.1× 126 1.2× 103 1.2× 35 0.5× 30 0.7× 34 635
Hui Cai China 13 424 2.3× 100 1.0× 247 2.9× 17 0.2× 19 0.4× 70 611
Fahad Albalawi Saudi Arabia 17 233 1.2× 93 0.9× 568 6.6× 39 0.5× 21 0.5× 47 818
Ammar Hussein Mutlag Iraq 11 368 2.0× 274 2.6× 157 1.8× 9 0.1× 57 1.3× 52 719
Xiaodan Liang China 14 216 1.1× 83 0.8× 113 1.3× 7 0.1× 66 1.5× 49 571
Sohom Chakrabarty India 13 170 0.9× 79 0.8× 462 5.4× 33 0.4× 31 0.7× 48 755
Mohsen Montazeri Iran 10 101 0.5× 121 1.2× 175 2.0× 11 0.1× 42 1.0× 31 467
Young-Sik Choi South Korea 12 303 1.6× 126 1.2× 251 2.9× 12 0.2× 127 3.0× 28 612
Koon Meng Ang Malaysia 8 92 0.5× 245 2.4× 90 1.0× 9 0.1× 48 1.1× 15 504

Countries citing papers authored by Apurva Narayan

Since Specialization
Citations

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

Fields of papers citing papers by Apurva Narayan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Apurva Narayan

This figure shows the co-authorship network connecting the top 25 collaborators of Apurva Narayan. A scholar is included among the top collaborators of Apurva Narayan 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 Apurva Narayan. Apurva Narayan 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.
2.
Narayan, Apurva, et al.. (2025). An EEG-based machine learning framework for diagnosing acute sleep deprivation. Frontiers in Physiology. 16. 1668129–1668129.
3.
Narayan, Apurva, et al.. (2024). Generating Universal Adversarial Perturbations for Quantum Classifiers. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 10891–10899.
4.
5.
Narayan, Apurva, et al.. (2024). AVATAR: Autonomous Vehicle Assessment Through Testing of Adversarial Patches in Real-Time. IEEE Transactions on Intelligent Vehicles. 10(5). 3208–3221.
6.
Kazemian, Negin, et al.. (2024). Long-Term Impact of Childhood Adversity on the Gut Microbiome of Nursing Students. International Journal of Environmental Research and Public Health. 21(1). 68–68. 2 indexed citations
7.
8.
9.
10.
Narayan, Apurva, et al.. (2023). Raman spectroscopy and convolutional neural networks for monitoring biochemical radiation response in breast tumour xenografts. Scientific Reports. 13(1). 1530–1530. 16 indexed citations
11.
12.
Narayan, Apurva, et al.. (2022). Novel Representative Sampling for Improved Active Learning. IFAC-PapersOnLine. 55(20). 55–60. 2 indexed citations
13.
Milani, Abbas S., et al.. (2022). Improving imbalanced dataset classification using Conditional Classifier-Generator (cCGen). 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 20. 671–675. 1 indexed citations
14.
Kazemian, Negin, et al.. (2021). Author Correction: The trans-kingdom battle between donor and recipient gut microbiome influences fecal microbiota transplantation outcome. Scientific Reports. 11(1). 4546–4546. 1 indexed citations
15.
Narayan, Apurva, et al.. (2021). Is Timing Critical to Trace Reconstruction?. 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2700–2705.
16.
Kazemian, Negin, et al.. (2020). The trans-kingdom battle between donor and recipient gut microbiome influences fecal microbiota transplantation outcome. Scientific Reports. 10(1). 18349–18349. 40 indexed citations
17.
Narayan, Apurva, et al.. (2020). QMine: A Framework for Mining Quantitative Regular Expressions from System Traces. 8977. 370–377. 2 indexed citations
18.
Narayan, Apurva, et al.. (2018). Mining Timed Regular Specifications from System Traces. ACM Transactions on Embedded Computing Systems. 17(2). 1–21. 16 indexed citations
19.
Schmidt, Lukas, Apurva Narayan, & Sebastian Fischmeister. (2017). TREM: A tool for mining timed regular specifications from system traces. 901–906. 6 indexed citations
20.
Narayan, Apurva & C. Patvardhan. (2009). A novel quantum evolutionary algorithm for quadratic Knapsack problem. 1388–1392. 10 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

Breakdown of academic impact, for papers by Xiaoli Xu Breakdown of academic impact, for papers by Huijun Liang Breakdown of academic impact, for papers by Hui Cai Breakdown of academic impact, for papers by Fahad Albalawi Breakdown of academic impact, for papers by Ammar Hussein Mutlag Breakdown of academic impact, for papers by Xiaodan Liang Breakdown of academic impact, for papers by Sohom Chakrabarty Breakdown of academic impact, for papers by Mohsen Montazeri Breakdown of academic impact, for papers by Young-Sik Choi Breakdown of academic impact, for papers by Koon Meng Ang
Rankless by CCL
2026