Sunil Gupta

2.0k total citations · 1 hit paper
43 papers, 1.3k citations indexed

About

Sunil Gupta is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability. According to data from OpenAlex, Sunil Gupta has authored 43 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 6 papers in Statistics and Probability. Recurrent topics in Sunil Gupta's work include Domain Adaptation and Few-Shot Learning (10 papers), Machine Learning in Healthcare (10 papers) and Bayesian Methods and Mixture Models (9 papers). Sunil Gupta is often cited by papers focused on Domain Adaptation and Few-Shot Learning (10 papers), Machine Learning in Healthcare (10 papers) and Bayesian Methods and Mixture Models (9 papers). Sunil Gupta collaborates with scholars based in Australia, United States and India. Sunil Gupta's co-authors include Svetha Venkatesh, Dinh Phung, Santu Rana, Truyen Tran, Wei Luo, Alistair Shilton, Nevenka Dimitrova, Tu Bao Ho, Chandan Karmakar and John Yearwood and has published in prestigious journals such as PLoS ONE, BMC Bioinformatics and Journal of Epidemiology & Community Health.

In The Last Decade

Sunil Gupta

42 papers receiving 1.3k 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.

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

2016 695 citations Wei Luo, Dinh Phung et al. Journal of Medical Internet Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sunil Gupta Australia	14	428	181	168	161	137	43	1.3k
Tu Bao Ho Japan	17	543 1.3×	175 1.0×	129 0.8×	119 0.7×	122 0.9×	82	1.6k
Alistair Shilton Australia	14	414 1.0×	168 0.9×	124 0.7×	114 0.7×	124 0.9×	36	1.3k
Carsten Eickhoff United States	20	710 1.7×	96 0.5×	120 0.7×	174 1.1×	182 1.3×	117	1.8k
Shyam Visweswaran United States	23	721 1.7×	109 0.6×	200 1.2×	181 1.1×	226 1.6×	129	1.9k
Yindalon Aphinyanaphongs United States	20	394 0.9×	190 1.0×	139 0.8×	179 1.1×	229 1.7×	64	2.3k
Ankur Teredesai United States	20	638 1.5×	270 1.5×	81 0.5×	218 1.4×	180 1.3×	83	1.6k
Zhe He United States	24	795 1.9×	157 0.9×	81 0.5×	172 1.1×	160 1.2×	203	2.3k
Guotong Xie China	23	616 1.4×	117 0.6×	413 2.5×	239 1.5×	86 0.6×	172	1.8k
Ahmed M. Alaa United States	20	511 1.2×	111 0.6×	251 1.5×	118 0.7×	174 1.3×	60	1.4k
Mark Hoogendoorn Netherlands	19	828 1.9×	81 0.4×	114 0.7×	308 1.9×	130 0.9×	138	1.9k

Countries citing papers authored by Sunil Gupta

Since Specialization

Citations

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

Fields of papers citing papers by Sunil Gupta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sunil Gupta

This figure shows the co-authorship network connecting the top 25 collaborators of Sunil Gupta. A scholar is included among the top collaborators of Sunil Gupta 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 Gupta. Sunil Gupta 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

Tawfik, Sherif Abdulkader, Tri Minh Nguyen, Salvy P. Russo, et al.. (2024). Embedding material graphs using the electron-ion potential: application to material fracture. Digital Discovery. 3(12). 2618–2627. 3 indexed citations

Han, Jin, Hiroko Fujimoto, Wu Yi Zheng, et al.. (2024). A web-based video messaging intervention for suicide prevention in men: study protocol for a five-armed randomised controlled trial. Trials. 25(1). 466–466.

Gupta, Sunil, et al.. (2024). Applications of Large Language Models in the Field of Suicide Prevention: Scoping Review. Journal of Medical Internet Research. 27. e63126–e63126. 7 indexed citations

Whitton, Alexis E., Wu Yi Zheng, Joanne R. Beames, et al.. (2023). Machine learning identifies a COVID-19-specific phenotype in university students using a mental health app. Internet Interventions. 34. 100666–100666. 3 indexed citations

Gupta, Sunil, et al.. (2022). Indian Agricultural Income – A Major Portion of The Indian Economy. 13(1). 43–49. 1 indexed citations

Jain, Dinesh Kumar, et al.. (2021). Identification of predictors and model for predicting prolonged length of stay in dengue patients. Health Care Management Science. 24(4). 786–798. 9 indexed citations

Shilton, Alistair, Sunil Gupta, Santu Rana, & Svetha Venkatesh. (2017). Regret bounds for transfer learning in Bayesian optimisation. Own your potential (DEAKIN). 307–315. 5 indexed citations

Luo, Wei, Dinh Phung, Truyen Tran, et al.. (2016). Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View. Journal of Medical Internet Research. 18(12). e323–e323. 695 indexed citations breakdown →

Gupta, Sunil, et al.. (2015). Stabilizingl1-norm prediction models by supervised feature grouping. Journal of Biomedical Informatics. 59. 149–168. 5 indexed citations

10.

Luo, Wei, Thin Nguyen, Melanie Nichols, et al.. (2015). Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset. PLoS ONE. 10(5). e0125602–e0125602. 20 indexed citations

11.

Rana, Santu, Sunil Gupta, & Svetha Venkatesh. (2015). Differentially Private Random Forest with High Utility. 955–960. 44 indexed citations

12.

Rana, Santu, Sunil Gupta, Dinh Phung, & Svetha Venkatesh. (2015). A predictive framework for modeling healthcare data with evolving clinical interventions. Statistical Analysis and Data Mining The ASA Data Science Journal. 8(3). 162–182. 8 indexed citations

13.

Gupta, Sunil, Truyen Tran, Wei Luo, et al.. (2014). Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry. BMJ Open. 4(3). e004007–e004007. 83 indexed citations

14.

Gupta, Sunil, et al.. (2014). Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso. Journal of Biomedical Informatics. 53. 277–290. 72 indexed citations

15.

Tran, Truyen, Wei Luo, Dinh Phung, et al.. (2014). A framework for feature extraction from hospital medical data with applications in risk prediction. BMC Bioinformatics. 15(1). 425–425. 30 indexed citations

16.

Gupta, Sunil, Dinh Phung, & Svetha Venkatesh. (2013). Factorial Multi-Task Learning : A Bayesian Nonparametric Approach. Deakin Research Online (Deakin University). 657–665. 15 indexed citations

17.

Gupta, Sunil, Dinh Phung, & Svetha Venkatesh. (2012). A nonparametric Bayesian Poisson Gamma model for count data. Deakin Research Online (Deakin University). 8 indexed citations

18.

Gupta, Sunil, Dinh Phung, & Svetha Venkatesh. (2012). A slice sampler for restricted hierarchical beta process with applications to shared subspace learning. Deakin Research Online (Deakin University). 316–325. 4 indexed citations

19.

Gupta, Sunil, Dinh Phung, & Svetha Venkatesh. (2012). A Bayesian Nonparametric Joint Factor Model for Learning Shared and Individual Subspaces from Multiple Data Sources. 200–211. 10 indexed citations

20.

Gupta, Sunil, Dinh Phung, Brett Adams, & Svetha Venkatesh. (2011). A matrix factorization framework for jointly analyzing multiple nonnegative data source. Deakin Research Online (Deakin University). 6–15. 2 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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