Kuljeet Singh

1.9k total citations
59 papers, 1.4k citations indexed

About

Kuljeet Singh is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Kuljeet Singh has authored 59 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 11 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Molecular Biology. Recurrent topics in Kuljeet Singh's work include COVID-19 diagnosis using AI (9 papers), Anomaly Detection Techniques and Applications (7 papers) and Growth Hormone and Insulin-like Growth Factors (6 papers). Kuljeet Singh is often cited by papers focused on COVID-19 diagnosis using AI (9 papers), Anomaly Detection Techniques and Applications (7 papers) and Growth Hormone and Insulin-like Growth Factors (6 papers). Kuljeet Singh collaborates with scholars based in India, New Zealand and United States. Kuljeet Singh's co-authors include K. Stelwagen, Martin Klempt, Peter D. Gluckman, Vibhakar Mansotra, Sourabh Shastri, Sachin Kumar, Chris Williams, Ernest Sirimanne, Jian Guan and Carina Mallard and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Biochemical and Biophysical Research Communications.

In The Last Decade

Kuljeet Singh

50 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kuljeet Singh India 18 329 235 206 186 178 59 1.4k
Ying Zhu China 21 433 1.3× 97 0.4× 82 0.4× 21 0.1× 66 0.4× 101 1.5k
Wen Dong China 30 1.5k 4.5× 33 0.1× 221 1.1× 81 0.4× 68 0.4× 142 3.2k
Mei Ma China 15 324 1.0× 19 0.1× 130 0.6× 106 0.6× 147 0.8× 86 996
Jun Ma China 24 408 1.2× 82 0.3× 291 1.4× 34 0.2× 87 0.5× 139 2.1k
Michael Wainberg Canada 21 844 2.6× 40 0.2× 115 0.6× 163 0.9× 417 2.3× 40 2.5k
Gregory Constantine United States 24 464 1.4× 112 0.5× 43 0.2× 28 0.2× 121 0.7× 64 2.2k
Doulaye Dembélé France 29 2.0k 6.0× 64 0.3× 39 0.2× 157 0.8× 253 1.4× 64 3.2k
Jon Havelock Canada 22 252 0.8× 152 0.6× 24 0.1× 110 0.6× 206 1.2× 54 1.7k
Aijun Liu China 22 564 1.7× 58 0.2× 95 0.5× 74 0.4× 62 0.3× 104 1.9k
Himanshu Arora United States 21 474 1.4× 109 0.5× 62 0.3× 60 0.3× 66 0.4× 87 1.5k

Countries citing papers authored by Kuljeet Singh

Since Specialization
Citations

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

Fields of papers citing papers by Kuljeet Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kuljeet Singh

This figure shows the co-authorship network connecting the top 25 collaborators of Kuljeet Singh. A scholar is included among the top collaborators of Kuljeet Singh 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 Kuljeet Singh. Kuljeet Singh 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.
Singh, Kuljeet, et al.. (2025). Deep CP-CXR: A Deep Learning Model for Classification of Covid-19 and Pneumonia Disease Using Chest X-Ray Images. Annals of Data Science. 1 indexed citations
2.
Singh, Kuljeet, et al.. (2025). Examining Daily Closing Price Prediction of the NSE Index using an Optimized Artificial Neural Network: A Study of Stock Market. Journal of Scientific Research. 17(1). 195–209. 1 indexed citations
3.
Sharma, Sandeep & Kuljeet Singh. (2023). Some Aspects of Rectifying Curves on Regular Surfaces Under Different Transformations. SHILAP Revista de lepidopterología. 21. 78–78. 2 indexed citations
4.
Kumar, Sachin, Sourabh Shastri, Kuljeet Singh, et al.. (2022). LiteCovidNet: A lightweight deep neural network model for detection of COVID‐19 using X‐ray images. International Journal of Imaging Systems and Technology. 32(5). 1464–1480. 21 indexed citations
5.
Shastri, Sourabh, et al.. (2022). CheXImageNet: a novel architecture for accurate classification of Covid-19 with chest x-ray digital images using deep convolutional neural networks. Health and Technology. 12(1). 193–204. 36 indexed citations
6.
Shastri, Sourabh, et al.. (2021). Deep-LSTM ensemble framework to forecast Covid-19: an insight to the global pandemic. International Journal of Information Technology. 13(4). 1291–1301. 45 indexed citations
7.
Shastri, Sourabh, et al.. (2021). GBoost: A novel Grading-AdaBoost ensemble approach for automatic identification of erythemato-squamous disease. International Journal of Information Technology. 13(3). 959–971. 11 indexed citations
8.
Shastri, Sourabh, et al.. (2021). CoBiD-net: a tailored deep learning ensemble model for time series forecasting of covid-19. Spatial Information Research. 30(1). 9–22. 15 indexed citations
9.
Shastri, Sourabh, et al.. (2020). Time series forecasting of Covid-19 using deep learning models: India-USA comparative case study. Chaos Solitons & Fractals. 140. 110227–110227. 175 indexed citations
10.
Shastri, Sourabh, et al.. (2020). A nested stacking ensemble model for predicting districts with high and low maternal mortality ratio (MMR) in India. International Journal of Information Technology. 13(2). 433–446. 7 indexed citations
11.
Singh, Kuljeet, et al.. (2019). Classification of Maternal Healthcare Data using Nave Bayes. International Journal of Computer Sciences and Engineering. 7(3). 388–394. 3 indexed citations
12.
Phyn, C.V.C., et al.. (2016). Tight Junction Protein Abundance and Apoptosis During Involution of Rat Mammary Glands. Journal of Cellular Physiology. 232(8). 2075–2082. 9 indexed citations
13.
Singh, Kuljeet, Christopher D. McMahon, Paul W. R. Harris, et al.. (2016). Maternally Administered Cyclic Glycine-Proline Increases Insulin-Like Growth Factor-1 Bioavailability and Novelty Recognition in Developing Offspring. Endocrinology. 157(8). 3130–3139. 20 indexed citations
14.
Johnson, Dave, et al.. (2014). Prenatal Maternal Genetic, Permanent Environmental And Paternal Epigenetic Effects In New Zealand Dairy Cattle. RUNE (Research UNE). 292. 1 indexed citations
15.
Stelwagen, K. & Kuljeet Singh. (2013). The Role of Tight Junctions in Mammary Gland Function. Journal of Mammary Gland Biology and Neoplasia. 19(1). 131–138. 120 indexed citations
16.
Singh, Kuljeet, I. Vetharaniam, Marina Prewitz, Jane Dobson, & K. Stelwagen. (2009). Understanding the interaction of prolactin and leukaemia inhibitory factor signalling during the switch from lactation to involution : Brief Communication. Proceedings of the New Zealand Society of Animal Production. 69. 65–67. 1 indexed citations
17.
Davis, et al.. (2007). Induced physical distension of rat mammary glands accelerates the onset of apoptosis and involution compared with milk accumulation alone : Brief Communication. Proceedings of the New Zealand Society of Animal Production. 67. 403–406. 4 indexed citations
18.
Stelwagen, K., et al.. (2004). Expression of the tight junction protein zonula occludens-1 during mammary engorgement. Proceedings of the New Zealand Society of Animal Production. 64. 43–47. 4 indexed citations
19.
McMahon, Christopher D., V. C. Farr, Kuljeet Singh, Thomas T. Wheeler, & Stephen Davis. (2004). Decreased expression of β1‐integrin and focal adhesion kinase in epithelial cells may initiate involution of mammary glands. Journal of Cellular Physiology. 200(2). 318–325. 26 indexed citations
20.
Sirimanne, Ernest, Alistair J. Gunn, Martin Klempt, et al.. (1992). Hypoxia-ischemia induces transforming growth factor β1 mRNA in the infant rat brain. Molecular Brain Research. 13(1-2). 93–101. 154 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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