Sat Gupta

2.6k total citations
116 papers, 1.9k citations indexed

About

Sat Gupta is a scholar working on Statistics and Probability, Artificial Intelligence and Epidemiology. According to data from OpenAlex, Sat Gupta has authored 116 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Statistics and Probability, 19 papers in Artificial Intelligence and 7 papers in Epidemiology. Recurrent topics in Sat Gupta's work include Survey Sampling and Estimation Techniques (92 papers), Statistical Methods and Bayesian Inference (17 papers) and Statistical Distribution Estimation and Applications (10 papers). Sat Gupta is often cited by papers focused on Survey Sampling and Estimation Techniques (92 papers), Statistical Methods and Bayesian Inference (17 papers) and Statistical Distribution Estimation and Applications (10 papers). Sat Gupta collaborates with scholars based in United States, Pakistan and India. Sat Gupta's co-authors include Javid Shabbir, Christopher J. Ruhm, Susan Letvak, Sarjinder Singh, David Harris, Bal Kishan Dass, Subhash Kumar Yadav, Bill Thornton, Mark R. Schulz and Daniel L. Bibeau and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Archaeological Science and The Journal of Nutritional Biochemistry.

In The Last Decade

Sat Gupta

105 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
Sat Gupta United States	24	1.3k	267	181	122	113	116	1.9k
Kirk M. Wolter United States	16	407 0.3×	110 0.4×	65 0.4×	127 1.0×	205 1.8×	37	981
Sonja D. Winter United States	11	177 0.1×	87 0.3×	111 0.6×	70 0.6×	67 0.6×	28	975
Getachew Dagne United States	19	298 0.2×	128 0.5×	183 1.0×	60 0.5×	69 0.6×	87	1.1k
Phillip S. Kott United States	15	444 0.3×	89 0.3×	70 0.4×	217 1.8×	51 0.5×	74	1.2k
Yeonseung Chung South Korea	20	168 0.1×	227 0.9×	113 0.6×	49 0.4×	52 0.5×	50	1.2k
D Holt United Kingdom	5	192 0.1×	130 0.5×	41 0.2×	148 1.2×	57 0.5×	8	738
Donald Olivier United States	13	196 0.1×	100 0.4×	93 0.5×	67 0.5×	37 0.3×	15	1.1k
Simon Grund Germany	16	193 0.1×	64 0.2×	43 0.2×	93 0.8×	29 0.3×	31	814
Caroline Beunckens Belgium	11	325 0.2×	31 0.1×	102 0.6×	40 0.3×	45 0.4×	17	810
Wei‐Ming Luh Taiwan	13	137 0.1×	197 0.7×	29 0.2×	105 0.9×	20 0.2×	47	808

Countries citing papers authored by Sat Gupta

Since Specialization

Citations

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

Fields of papers citing papers by Sat Gupta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sat Gupta

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

Al‐Essa, Laila A., et al.. (2025). An application of modified systematic sampling in auto-correlated populations. Kuwait Journal of Science. 52(3). 100404–100404. 1 indexed citations

Parker, Michael H., et al.. (2025). Impact of Auxiliary Information and Measurement Errors on Mean Estimation with Mixture Optional Enhanced Trust (MOET) Randomized Response Model. Axioms. 14(3). 183–183.

Gupta, Sat, et al.. (2024). Accounting for Measurement Error and Untruthfulness in Binary RRT Models. Mathematics. 12(6). 875–875. 1 indexed citations

Gupta, Sat, Michael H. Parker, & Sadia Khalil. (2024). A Ratio Estimator for the Mean Using a Mixture Optional Enhance Trust (MOET) Randomized Response Model. Mathematics. 12(22). 3617–3617.

Gupta, Sat, et al.. (2022). Accounting for Lack of Trust in Optional Binary RRT Models Using a Unified Measure of Privacy and Efficiency. Journal of Statistical Theory and Practice. 16(3).

Gupta, Sat, et al.. (2022). Correction to: Accounting for Lack of Trust in Optional Binary RRT Models Using a Unified Measure of Privacy and Efficiency. Journal of Statistical Theory and Practice. 16(4). 1 indexed citations

Shabbir, Javid, et al.. (2022). Predictive Estimation of Population Mean in Ranked Set Sampling. SHILAP Revista de lepidopterología. 5 indexed citations

Shabbir, Javid, Zahida Iqbal, & Sat Gupta. (2021). On distribution function under two-phase stratified sampling using two auxiliary variables for mean estimation. Communications in Statistics - Simulation and Computation. 52(8). 3758–3770.

Shabbir, Javid, et al.. (2020). An optimal systematic sampling scheme. Journal of Statistical Computation and Simulation. 90(11). 2023–2036. 1 indexed citations

10.

Yadav, Subhash Kumar, et al.. (2016). Modified Ratio and Product Estimators for Estimating Population Mean in Two-Phase Sampling. 6(3). 61–68. 8 indexed citations

11.

Gupta, Sat & Javid Shabbir. (2015). Estimation of Finite Population Mean in Stratified Random Sampling with Two Auxiliary Variables under Double Sampling Design. Communication in Statistics- Theory and Methods. 44(13). 2798–2808. 3 indexed citations

12.

Schulz, Mark R., et al.. (2014). Does providing nutrition information at vending machines reduce calories per item sold?. Journal of Public Health Policy. 36(1). 110–122. 28 indexed citations

13.

Schulz, Mark R., et al.. (2014). Factors Related to the Number of Fast Food Meals Obtained by College Meal Plan Students. Journal of American College Health. 62(8). 562–569. 24 indexed citations

14.

Letvak, Susan, Christopher J. Ruhm, & Sat Gupta. (2012). Original Research. AJN American Journal of Nursing. 112(2). 30–38. 257 indexed citations

15.

Shabbir, Javid & Sat Gupta. (2010). Estimation of the Finite Population Mean in Two Phase Sampling when Auxiliary Variables are Attributes. Quality Engineering. 39(1). 121–129. 3 indexed citations

16.

Shabbir, Javid, et al.. (2010). Ratio Estimation of the Mean of a Sensitive Variable in the Presence of Auxiliary Information. Journal of Statistical Theory and Practice. 4(3). 495–507. 52 indexed citations

17.

Shabbir, Javid & Sat Gupta. (2007). On Improvement in Variance Estimation Using Auxiliary Information. Communication in Statistics- Theory and Methods. 36(12). 2177–2185. 63 indexed citations

18.

Gupta, Sat & Javid Shabbir. (2007). Sensitivity estimation for personal interview survey questions. SHILAP Revista de lepidopterología. 30 indexed citations

19.

Gupta, Sat, et al.. (2006). Predictors of student success in entry-level undergraduate mathematics courses.. College student journal. 40(1). 97–108. 15 indexed citations

20.

Gupta, Sat & Javid Shabbir. (2005). An Alternative to Warner’s Randomized Response Model. Journal of Modern Applied Statistical Methods. 5(2). 328–331. 5 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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