Saptarshi Sengupta

955 total citations · 1 hit paper
29 papers, 588 citations indexed

About

Saptarshi Sengupta is a scholar working on Artificial Intelligence, Computer Networks and Communications and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Saptarshi Sengupta has authored 29 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 4 papers in Computer Networks and Communications and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Saptarshi Sengupta's work include Metaheuristic Optimization Algorithms Research (7 papers), Topic Modeling (5 papers) and Advanced Text Analysis Techniques (3 papers). Saptarshi Sengupta is often cited by papers focused on Metaheuristic Optimization Algorithms Research (7 papers), Topic Modeling (5 papers) and Advanced Text Analysis Techniques (3 papers). Saptarshi Sengupta collaborates with scholars based in United States, India and South Africa. Saptarshi Sengupta's co-authors include Sanchita Basak, Richard Alan Peters, Srikanth Prabhu, Papita Das, Chiranjib Bhattacharjee, Krishnaraj Chadaga, Lopamudra Das, Avijit Bhowal, Adam Pickens and Niranjana Sampathila and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Knowledge-Based Systems.

In The Last Decade

Saptarshi Sengupta

27 papers receiving 564 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.

Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives

2018 345 citations Saptarshi Sengupta, Sanchita Basak et al. Machine Learning and Knowledge Extraction profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Saptarshi Sengupta United States	10	206	83	75	70	55	29	588
Sanghoun Oh South Korea	8	173 0.8×	141 1.7×	69 0.9×	37 0.5×	74 1.3×	18	558
Bai Qing-hai China	5	177 0.9×	142 1.7×	104 1.4×	49 0.7×	40 0.7×	10	584
André Luis Debiaso Rossi Brazil	11	361 1.8×	69 0.8×	55 0.7×	100 1.4×	45 0.8×	32	720
G. Maragatham India	9	166 0.8×	77 0.9×	41 0.5×	107 1.5×	25 0.5×	39	614
Ecir Uğur Küçüksille Türkiye	11	284 1.4×	80 1.0×	49 0.7×	44 0.6×	92 1.7×	58	645
Haoyue Liu China	9	377 1.8×	57 0.7×	46 0.6×	75 1.1×	38 0.7×	18	698
Khalid Almohammadi Saudi Arabia	9	203 1.0×	112 1.3×	57 0.8×	58 0.8×	42 0.8×	23	648
Laila Abdel‐Fatah Egypt	8	209 1.0×	136 1.6×	62 0.8×	50 0.7×	77 1.4×	11	578
Sanchita Basak United States	7	154 0.7×	82 1.0×	79 1.1×	48 0.7×	53 1.0×	13	431
Bilal India	6	319 1.5×	108 1.3×	100 1.3×	54 0.8×	174 3.2×	10	691

Countries citing papers authored by Saptarshi Sengupta

Since Specialization

Citations

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

Fields of papers citing papers by Saptarshi Sengupta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saptarshi Sengupta

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

All Works

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20 of 20 papers shown

Sengupta, Saptarshi, et al.. (2025). Deep Learning for Non-Invasive Blood Pressure Monitoring: Model Performance and Quantization Trade-Offs. Electronics. 14(7). 1300–1300. 1 indexed citations

Gupta, S. K., et al.. (2025). Survival Analysis for Cancers of the Brain, CNS and Bone using Retrieval Augmented Generation on the SEER Database. Proceedings of the AAAI Symposium Series. 5(1). 31–36.

Sengupta, Saptarshi, et al.. (2024). Adversarial Attacks and Defenses in Multivariate Time-Series Forecasting for Smart and Connected Infrastructures. Annual Conference of the PHM Society. 16(1). 1 indexed citations

Sengupta, Saptarshi, et al.. (2024). Towards Efficient Methods in Medical Question Answering using Knowledge Graph Embeddings. 5089–5096.

Sengupta, Saptarshi, et al.. (2023). Large-scale End-of-Life Prediction of Hard Disks in Distributed Datacenters. 27. 261–266. 3 indexed citations

Prakash, Krishna, et al.. (2023). 2D-3D Facial Image Analysis for Identification of Facial Features Using Machine Learning Algorithms With Hyper-Parameter Optimization for Forensics Applications. IEEE Access. 11. 82521–82538. 13 indexed citations

Prabhu, Srikanth, et al.. (2022). Supervised Learning Models for the Preliminary Detection of COVID-19 in Patients Using Demographic and Epidemiological Parameters. Information. 13(7). 330–330. 24 indexed citations

Prabhu, Srikanth, et al.. (2022). Use of Machine Learning for Early Detection of Knee Osteoarthritis and Quantifying Effectiveness of Treatment Using Force Platform. Journal of Sensor and Actuator Networks. 11(3). 48–48. 9 indexed citations

Prabhu, Srikanth, et al.. (2022). Incorporating a Machine Learning Model into a Web-Based Administrative Decision Support Tool for Predicting Workplace Absenteeism. Information. 13(7). 320–320. 2 indexed citations

10.

Li, Yang, et al.. (2022). An interactive web-based tool for predicting and exploring brain cancer survivability. SHILAP Revista de lepidopterología. 3. 100132–100132. 6 indexed citations

11.

Chadaga, Krishnaraj, Srikanth Prabhu, Niranjana Sampathila, et al.. (2022). Predicting cervical cancer biopsy results using demographic and epidemiological parameters: a custom stacked ensemble machine learning approach. Cogent Engineering. 9(1). 24 indexed citations

12.

Pickens, Adam & Saptarshi Sengupta. (2021). Benchmarking Studies Aimed at Clustering and Classification Tasks Using K-Means, Fuzzy C-Means and Evolutionary Neural Networks. SHILAP Revista de lepidopterología. 3(3). 695–719. 13 indexed citations

13.

Prabhu, Srikanth, et al.. (2021). Remaining Useful Life Estimation of Hard Disk Drives using Bidirectional LSTM Networks. 2021 IEEE International Conference on Big Data (Big Data). 4832–4841. 5 indexed citations

14.

Basak, Sanchita, Saptarshi Sengupta, Shi-Jie Wen, & Abhishek Dubey. (2020). Spatio-temporal AI inference engine for estimating hard disk reliability. Pervasive and Mobile Computing. 70. 101283–101283. 8 indexed citations

15.

Sengupta, Saptarshi, Sanchita Basak, & Richard Alan Peters. (2019). Chaotic Quantum Double Delta Swarm Algorithm Using Chebyshev Maps: Theoretical Foundations, Performance Analyses and Convergence Issues. Journal of Sensor and Actuator Networks. 8(1). 9–9. 3 indexed citations

16.

Sengupta, Saptarshi, et al.. (2019). Improving Semantic Similarity with Cross-Lingual Resources: A Study in Bangla—A Low Resourced Language. Informatics. 6(2). 19–19. 8 indexed citations

17.

Basak, Sanchita, Saptarshi Sengupta, & Abhishek Dubey. (2018). A Data-driven Prognostic Architecture for Online Monitoring of Hard Disks Using Deep LSTM Networks.. arXiv (Cornell University). 1 indexed citations

18.

Sengupta, Saptarshi, Sanchita Basak, & Richard Alan Peters. (2018). Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives. Machine Learning and Knowledge Extraction. 1(1). 157–191. 345 indexed citations breakdown →

19.

Sengupta, Saptarshi, Sanchita Basak, & Richard Alan Peters. (2018). Data Clustering using a Hybrid of Fuzzy C-Means and Quantum-behaved Particle Swarm Optimization. arXiv (Cornell University). 137–142. 18 indexed citations

20.

Sengupta, Saptarshi, et al.. (2017). Classification of male and female speech using perceptual features. 18. 1–7. 6 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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