Rounak Dey

3.6k total citations · 1 hit paper
17 papers, 822 citations indexed

About

Rounak Dey is a scholar working on Genetics, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Rounak Dey has authored 17 papers receiving a total of 822 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Genetics, 5 papers in Molecular Biology and 3 papers in Infectious Diseases. Recurrent topics in Rounak Dey's work include Genetic Associations and Epidemiology (9 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and COVID-19 epidemiological studies (3 papers). Rounak Dey is often cited by papers focused on Genetic Associations and Epidemiology (9 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and COVID-19 epidemiological studies (3 papers). Rounak Dey collaborates with scholars based in United States, South Korea and Australia. Rounak Dey's co-authors include Seunggeun Lee, Gonçalo R. Abecasis, Wei Zhou, Lars G. Fritsche, Cristen J. Willer, Jonas B. Nielsen, Joshua C. Denny, Sarah A. Gagliano Taliun, Maoxuan Lin and Lisa A. Bastarache and has published in prestigious journals such as Nature Communications, Nature Genetics and Journal of the American Statistical Association.

In The Last Decade

Rounak Dey

16 papers receiving 818 citations

Hit Papers

Efficiently controlling for case-control imbalance and sa... 2018 2026 2020 2023 2018 100 200 300 400 500
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.

  1. Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies
    2018 596 citations Wei Zhou, Jonas B. Nielsen et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rounak Dey United States 8 486 279 97 62 61 17 822
Jonathon LeFaive United States 8 462 1.0× 283 1.0× 94 1.0× 75 1.2× 63 1.0× 10 793
Brooke N. Wolford United States 7 391 0.8× 251 0.9× 79 0.8× 67 1.1× 78 1.3× 12 759
Kathryn S. Burch United States 10 514 1.1× 309 1.1× 60 0.6× 63 1.0× 42 0.7× 14 826
Peter VandeHaar United States 8 526 1.1× 328 1.2× 116 1.2× 78 1.3× 82 1.3× 9 937
Malika Freund United States 7 527 1.1× 410 1.5× 61 0.6× 79 1.3× 38 0.6× 10 882
Priit Palta Estonia 16 438 0.9× 381 1.4× 71 0.7× 97 1.6× 71 1.2× 43 951
Joshua Backman United States 7 315 0.6× 177 0.6× 73 0.8× 32 0.5× 68 1.1× 9 605
Juan Carlos Fernández-López Mexico 14 250 0.5× 177 0.6× 63 0.6× 65 1.0× 41 0.7× 27 694
Tanya N. Nelson Canada 21 450 0.9× 308 1.1× 45 0.5× 24 0.4× 65 1.1× 51 1.0k
Anthony Marcketta United States 4 313 0.6× 158 0.6× 65 0.7× 28 0.5× 47 0.8× 7 537

Countries citing papers authored by Rounak Dey

Since Specialization
Citations

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

Fields of papers citing papers by Rounak Dey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rounak Dey

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

All Works

17 of 17 papers shown
1.
Dey, Rounak, et al.. (2025). AI-Driven Machine Learning for Fraud Detection and Risk Management in U.S. Healthcare Billing and Insurance. Journal of Computer Science and Technology Studies. 7(1). 188–198. 4 indexed citations
2.
McCaw, Zachary R., Rounak Dey, David Amar, et al.. (2025). Pitfalls in performing genome-wide association studies on ratio traits. Human Genetics and Genomics Advances. 6(2). 100406–100406.
3.
Sarkar, Malay, et al.. (2025). Artificial Intelligence in telemedicine and remote patient monitoring: Enhancing virtual healthcare through AI-driven diagnostic and predictive technologies. International Journal of Science and Research Archive. 15(2). 1046–1055. 2 indexed citations
4.
Wang, Xinan, Joao V. Alessi, Xihao Li, et al.. (2024). Additional impact of genetic ancestry over race/ethnicity to prevalence of KRAS mutations and allele-specific subtypes in non-small cell lung cancer. Human Genetics and Genomics Advances. 5(3). 100320–100320. 2 indexed citations
5.
Shyr, Derek, Rounak Dey, Xihao Li, et al.. (2024). Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies. The American Journal of Human Genetics. 111(10). 2129–2138. 3 indexed citations
6.
Gaynor, Sheila M., et al.. (2022). COVID-19 Spread Mapper: a multi-resolution, unified framework and open-source tool. Bioinformatics. 38(9). 2661–2663. 7 indexed citations
7.
Hong, David, Rounak Dey, Xihong Lin, Brian Cleary, & Edgar Dobriban. (2022). Group testing via hypergraph factorization applied to COVID-19. Nature Communications. 13(1). 1837–1837. 4 indexed citations
8.
Dey, Rounak, Wei Zhou, Tuomo Kiiskinen, et al.. (2022). Efficient and accurate frailty model approach for genome-wide survival association analysis in large-scale biobanks. Nature Communications. 13(1). 5437–5437. 14 indexed citations
9.
Bi, Wenjian, Wei Zhou, Rounak Dey, et al.. (2021). Efficient mixed model approach for large-scale genome-wide association studies of ordinal categorical phenotypes. The American Journal of Human Genetics. 108(5). 825–839. 30 indexed citations
10.
Quick, Corbin, Rounak Dey, & Xihong Lin. (2021). Rejoinder: Regression Models for Understanding COVID-19 Epidemic Dynamics With Incomplete Data. Journal of the American Statistical Association. 116(536). 1591–1594. 1 indexed citations
11.
Quick, Corbin, Rounak Dey, & Xihong Lin. (2021). Regression Models for Understanding COVID-19 Epidemic Dynamics With Incomplete Data. Journal of the American Statistical Association. 116(536). 1561–1577. 17 indexed citations
12.
Zhang, Daiwei, Rounak Dey, & Seunggeun Lee. (2020). Fast and robust ancestry prediction using principal component analysis. Bioinformatics. 36(11). 3439–3446. 23 indexed citations
13.
Bi, Wenjian, Zhangchen Zhao, Rounak Dey, et al.. (2019). A Fast and Accurate Method for Genome-wide Scale Phenome-wide G × E Analysis and Its Application to UK Biobank. The American Journal of Human Genetics. 105(6). 1182–1192. 20 indexed citations
14.
Dey, Rounak & Seunggeun Lee. (2019). Asymptotic properties of principal component analysis and shrinkage-bias adjustment under the generalized spiked population model. Journal of Multivariate Analysis. 173. 145–164. 5 indexed citations
15.
Dey, Rounak, Jonas B. Nielsen, Lars G. Fritsche, et al.. (2019). Robust meta‐analysis of biobank‐based genome‐wide association studies with unbalanced binary phenotypes. Genetic Epidemiology. 43(5). 462–476. 7 indexed citations
16.
Zhou, Wei, Jonas B. Nielsen, Lars G. Fritsche, et al.. (2018). Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nature Genetics. 50(9). 1335–1341. 596 indexed citations breakdown →
17.
Dey, Rounak, Ellen M. Schmidt, Gonçalo R. Abecasis, & Seunggeun Lee. (2017). A Fast and Accurate Algorithm to Test for Binary Phenotypes and Its Application to PheWAS. The American Journal of Human Genetics. 101(1). 37–49. 87 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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