Sunil Kumar Jha

2.6k total citations
103 papers, 2.0k citations indexed

About

Sunil Kumar Jha is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Sunil Kumar Jha has authored 103 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Biomedical Engineering, 22 papers in Computer Vision and Pattern Recognition and 14 papers in Artificial Intelligence. Recurrent topics in Sunil Kumar Jha's work include Advanced Chemical Sensor Technologies (26 papers), Digital Media Forensic Detection (14 papers) and Insect Pheromone Research and Control (11 papers). Sunil Kumar Jha is often cited by papers focused on Advanced Chemical Sensor Technologies (26 papers), Digital Media Forensic Detection (14 papers) and Insect Pheromone Research and Control (11 papers). Sunil Kumar Jha collaborates with scholars based in China, United States and India. Sunil Kumar Jha's co-authors include Kenshi Hayashi, R. D. S. Yadava, Nilesh Patel, Ehsan Elahi, Han Zhang, Anju Jha, Jinwei Wang, Xiangyang Luo, Xiaorui Zhang and Yun-Qing Shi and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Chemosphere and IEEE Access.

In The Last Decade

Sunil Kumar Jha

96 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sunil Kumar Jha China	22	420	376	359	283	127	103	2.0k
Qi Li China	23	188 0.4×	396 1.1×	152 0.4×	243 0.9×	79 0.6×	153	2.1k
Xiaoyi Wang China	28	186 0.4×	428 1.1×	392 1.1×	505 1.8×	70 0.6×	231	2.5k
Jingjing Chen China	28	184 0.4×	952 2.5×	138 0.4×	327 1.2×	68 0.5×	180	2.6k
Muhammad Syafrudin South Korea	24	221 0.5×	174 0.5×	189 0.5×	564 2.0×	84 0.7×	114	2.7k
Humaira Arshad Pakistan	14	270 0.6×	541 1.4×	228 0.6×	788 2.8×	69 0.5×	23	3.0k
Lei Chen China	23	285 0.7×	219 0.6×	161 0.4×	594 2.1×	68 0.5×	219	2.4k
Oludare Isaac Abiodun Nigeria	12	270 0.6×	535 1.4×	225 0.6×	869 3.1×	71 0.6×	18	3.1k
Abiodun Esther Omolara Malaysia	15	275 0.7×	551 1.5×	258 0.7×	883 3.1×	72 0.6×	26	3.2k
Nachaat Mohamed India	14	221 0.5×	444 1.2×	148 0.4×	654 2.3×	61 0.5×	49	2.4k
Asdrúbal López‐Chau Mexico	12	159 0.4×	198 0.5×	374 1.0×	639 2.3×	139 1.1×	61	2.1k

Countries citing papers authored by Sunil Kumar Jha

Since Specialization

Citations

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

Fields of papers citing papers by Sunil Kumar Jha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunil Kumar Jha. 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 Sunil Kumar Jha. The network helps show where Sunil Kumar Jha may publish in the future.

Co-authorship network of co-authors of Sunil Kumar Jha

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Singh, Ankita, et al.. (2025). A compact hand-held continuum manipulator for minimally invasive neurosurgery. Journal of Robotic Surgery. 20(1). 56–56.

Patel, Nitin, et al.. (2025). Deep learning for automated defect recognition in tungsten inert gas welds of stainless steel 304. Measurement. 253. 117850–117850. 4 indexed citations

Zhang, Xiaorui, et al.. (2024). A novel noiselayer-decoder driven blind watermarking network. Displays. 85. 102823–102823. 2 indexed citations

Tanna, Jay A., et al.. (2023). Heat Pulse Probe-Based Smart Soil Moisture Detection System. IEEE Sensors Journal. 23(11). 11428–11436. 1 indexed citations

Jha, Sunil Kumar, et al.. (2023). Comparative studies of functional groups present in invasive and economically important plant leaf methanolic extracts by using FTIR spectroscopic analysis. GSC Biological and Pharmaceutical Sciences. 23(3). 184–191.

Zhang, Xiaorui, et al.. (2022). A Real-time Cutting Model Based on Finite Element and Order Reduction. Computer Systems Science and Engineering. 43(1). 1–15. 21 indexed citations

Ahmad, Zulfiqar, et al.. (2021). Optimization of biotic and abiotic factors liable for biodegradation of chlorpyrifos and their modeling using neural network approaches. Applied Soil Ecology. 166. 103990–103990. 14 indexed citations

Wang, Jinwei, et al.. (2021). SmsNet: A New Deep Convolutional Neural Network Model for Adversarial Example Detection. IEEE Transactions on Multimedia. 24. 230–244. 25 indexed citations

Zhang, Xiaorui, Xun Sun, Wei Sun, et al.. (2021). Deformation Expression of Soft Tissue Based on BP Neural Network. Intelligent Automation & Soft Computing. 32(2). 1041–1053. 92 indexed citations

10.

Zhang, Xiaorui, et al.. (2021). A Fast and Accurate Vascular Tissue Simulation Model Based on Point Primitive Method. Intelligent Automation & Soft Computing. 27(3). 873–889. 16 indexed citations

11.

Jha, Sunil Kumar, Ninoslav Marina, Jinwei Wang, & Zulfiqar Ahmad. (2021). A hybrid machine learning approach of fuzzy-rough-k-nearest neighbor, latent semantic analysis, and ranker search for efficient disease diagnosis. Journal of Intelligent & Fuzzy Systems. 42(3). 2549–2563. 4 indexed citations

12.

Li, Qing, et al.. (2020). Exploring multi-level motivations towards green design practices: A system dynamics approach. Sustainable Cities and Society. 64. 102490–102490. 28 indexed citations

13.

Wang, Jinwei, et al.. (2019). Quaternion Convolutional Neural Network for Color Image Classification and Forensics. IEEE Access. 7. 20293–20301. 52 indexed citations

14.

Jha, Sunil Kumar, Zhaoqing Pan, Ehsan Elahi, & Nilesh Patel. (2018). A comprehensive search for expert classification methods in disease diagnosis and prediction. Expert Systems. 36(1). 31 indexed citations

15.

Jha, Sunil Kumar. (2016). Characterization of human body odor and identification of aldehydes using chemical sensor. Reviews in Analytical Chemistry. 36(2). 21 indexed citations

16.

Jha, Sunil Kumar, et al.. (2014). Data fusion approach for human body odor discrimination using GC-MS spectra. 1–6. 10 indexed citations

17.

Jha, Sunil Kumar, et al.. (2011). Updating river bathymetry with multiple data sources using kriging. AGU Fall Meeting Abstracts. 2011. 1 indexed citations

18.

Ray, Amitava, et al.. (1997). The ancient 11th century iron pillar at Dhar, India: a microstructural insight into material characteristics. Journal of Materials Science Letters. 16(5). 371–375. 3 indexed citations

19.

Jha, Sunil Kumar. (1986). The nasal vowels in Maithili: an acoustic study. Journal of Phonetics. 14(2). 223–230. 4 indexed citations

20.

Jha, Sunil Kumar. (1985). Acoustic analysis of the Maithili diphthongs. Journal of Phonetics. 13(1). 107–115. 18 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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