Saurabh Agarwal

1.2k total citations
88 papers, 496 citations indexed

About

Saurabh Agarwal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Saurabh Agarwal has authored 88 papers receiving a total of 496 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 12 papers in Media Technology. Recurrent topics in Saurabh Agarwal's work include Digital Media Forensic Detection (29 papers), Advanced Steganography and Watermarking Techniques (24 papers) and Generative Adversarial Networks and Image Synthesis (8 papers). Saurabh Agarwal is often cited by papers focused on Digital Media Forensic Detection (29 papers), Advanced Steganography and Watermarking Techniques (24 papers) and Generative Adversarial Networks and Image Synthesis (8 papers). Saurabh Agarwal collaborates with scholars based in India, South Korea and United States. Saurabh Agarwal's co-authors include Satish Chand, Rajesh Kumar, Ki‐Hyun Jung, Dilip Kumar Sharma, Hyunsung Kim, John T. Novak, Mohammad Abu‐Orf, A. Sujil, Amel Ali Alhussan and Hanaa A. Abdallah and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Research and Scientific Reports.

In The Last Decade

Saurabh Agarwal

75 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
Saurabh Agarwal India 12 153 119 52 50 49 88 496
Raihan Ul Islam Bangladesh 11 143 0.9× 158 1.3× 34 0.7× 52 1.0× 36 0.7× 42 493
Jiafa Mao China 13 173 1.1× 115 1.0× 27 0.5× 20 0.4× 22 0.4× 50 365
K. Sakthidasan Sankaran India 14 185 1.2× 118 1.0× 91 1.8× 71 1.4× 42 0.9× 71 592
Jamal Ahmad Dargham Malaysia 13 182 1.2× 81 0.7× 112 2.2× 69 1.4× 31 0.6× 53 538
Ji-Won Baek South Korea 12 85 0.6× 112 0.9× 84 1.6× 15 0.3× 25 0.5× 41 416
Tianwei Xu China 11 98 0.6× 87 0.7× 24 0.5× 33 0.7× 28 0.6× 53 371
Oumaima Saidani Saudi Arabia 15 113 0.7× 200 1.7× 36 0.7× 25 0.5× 13 0.3× 58 521
Kanwarpartap Singh Gill India 10 83 0.5× 155 1.3× 31 0.6× 14 0.3× 19 0.4× 192 662
M. Z. Rashad Egypt 14 108 0.7× 200 1.7× 112 2.2× 57 1.1× 18 0.4× 56 548
Yaganteeswarudu Akkem India 6 83 0.5× 151 1.3× 27 0.5× 33 0.7× 21 0.4× 11 505

Countries citing papers authored by Saurabh Agarwal

Since Specialization
Citations

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

Fields of papers citing papers by Saurabh Agarwal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saurabh Agarwal

This figure shows the co-authorship network connecting the top 25 collaborators of Saurabh Agarwal. A scholar is included among the top collaborators of Saurabh Agarwal 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 Saurabh Agarwal. Saurabh Agarwal 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
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2.
Mobayen, Saleh, Ehsanolah Assareh, Nima Izadyar, et al.. (2025). Multi-functional hybrid energy system for zero-energy residential buildings: Integrating hydrogen production and renewable energy solutions. International Journal of Hydrogen Energy. 102. 647–672. 11 indexed citations
3.
Assareh, Ehsanolah, Jagadeesh Kumar Alagarasan, Mehdi Hosseinzadeh, et al.. (2025). Dynamic Simulation and Optimization of an Innovative Cogeneration System Using TRNSYS, EES, and Response Surface Methodology as a Machine learning method. Journal of the Taiwan Institute of Chemical Engineers. 180. 106461–106461. 1 indexed citations
4.
Mohan, Hari, Joon Yoo, Saurabh Agarwal, & Neha Agarwal. (2025). LightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection. Bioengineering. 12(1). 73–73. 3 indexed citations
5.
Assareh, Ehsanolah, et al.. (2025). Optimization of solar farm design for energy efficiency in university campuses using machine learning: A case study. Engineering Applications of Artificial Intelligence. 153. 110847–110847. 2 indexed citations
6.
Assareh, Ehsanolah, Mohammad Firoozzadeh, Saurabh Agarwal, et al.. (2024). Machine learning optimization of a zero energy building (ZEB) by waste heat recovery in a co-generation system. Energy and Buildings. 323. 114711–114711. 2 indexed citations
7.
Gambo, Ishaya, et al.. (2024). Identifying and resolving conflict in mobile application features through contradictory feedback analysis. Heliyon. 10(17). e36729–e36729. 5 indexed citations
8.
Agarwal, Saurabh & Ki‐Hyun Jung. (2024). Digital image steganalysis using entropy driven deep neural network. Journal of Information Security and Applications. 84. 103799–103799. 2 indexed citations
9.
10.
Rao, S. Koteswara, et al.. (2024). Radar-Based Target Tracking Using Deep Learning Approaches with Unscented Kalman Filter. Applied Sciences. 14(18). 8332–8332. 5 indexed citations
11.
Wasti, Bram, Liangzhen Lai, Anas Mahmoud, et al.. (2024). LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding. 12622–12642. 7 indexed citations
12.
Gambo, Ishaya, et al.. (2024). Enhancing User Trust and Interpretability in AI-Driven Feature Request Detection for Mobile App Reviews: An Explainable Approach. IEEE Access. 12. 114023–114045. 7 indexed citations
13.
Кумар, Арун, Hari Om, Satish Chand, & Saurabh Agarwal. (2023). Reversible data hiding in encrypted image using two-pass pixel value ordering. Journal of Information Security and Applications. 76. 103545–103545. 3 indexed citations
14.
Agarwal, Saurabh, et al.. (2023). Detecting Images in Two-Operator Series Manipulation: A Novel Approach Using Transposed Convolution and Information Fusion. Symmetry. 15(10). 1898–1898. 1 indexed citations
15.
Agarwal, Saurabh & Ki‐Hyun Jung. (2023). Median filtering detection using optimal multi-direction threshold on higher-order difference pixels. Multimedia Tools and Applications. 82(20). 30875–30893. 2 indexed citations
16.
Gupta, Himanshu, Om Prakash Verma, Tarun Kumar Sharma, et al.. (2022). Automatic Rice Disease Detection and Assistance Framework Using Deep Learning and a Chatbot. Electronics. 11(14). 2110–2110. 26 indexed citations
17.
Agarwal, Saurabh, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, & Dimitris Papailiopoulos. (2021). Adaptive Gradient Communication via Critical Learning Regime Identification. 3. 55–80. 5 indexed citations
18.
Rao, Nikhil, et al.. (2020). Regularized Graph Convolutional Networks for Short Text Classification. 236–242. 9 indexed citations
19.
Agarwal, Saurabh & Satish Chand. (2015). Anti-Forensics of JPEG Images using Interpolation. International Journal of Image Graphics and Signal Processing. 7(12). 10. 2 indexed citations
20.
Agarwal, Saurabh & Satish Chand. (2015). Image Forgery Detection using Multi Scale Entropy Filter and Local Phase Quantization. International Journal of Image Graphics and Signal Processing. 7(10). 78. 19 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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