Rajen D. Shah

819 total citations
28 papers, 347 citations indexed

About

Rajen D. Shah is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Rajen D. Shah has authored 28 papers receiving a total of 347 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Statistics and Probability, 4 papers in Artificial Intelligence and 3 papers in Molecular Biology. Recurrent topics in Rajen D. Shah's work include Statistical Methods and Inference (13 papers), Statistical Methods and Bayesian Inference (8 papers) and Advanced Statistical Methods and Models (6 papers). Rajen D. Shah is often cited by papers focused on Statistical Methods and Inference (13 papers), Statistical Methods and Bayesian Inference (8 papers) and Advanced Statistical Methods and Models (6 papers). Rajen D. Shah collaborates with scholars based in United Kingdom, United States and Switzerland. Rajen D. Shah's co-authors include Jonas Peters, Larry L. Augsburger, David G. Pope, Peter Bühlmann, Nicolai Meinshausen, Qingyuan Zhao, Sergio Bacallado, Raman Iyer, Tim J. Stevens and Cristina Robles and has published in prestigious journals such as Journal of the American Statistical Association, PLoS Biology and International Journal of Pharmaceutics.

In The Last Decade

Rajen D. Shah

24 papers receiving 332 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rajen D. Shah United Kingdom 10 107 87 82 81 27 28 347
Kamlesh Kumar Shukla India 11 164 1.5× 40 0.5× 4 0.0× 74 0.9× 10 0.4× 75 355
John Mack Australia 10 11 0.1× 42 0.5× 8 0.1× 18 0.2× 3 0.1× 22 315
Shlomo Reisner Israel 11 32 0.3× 4 0.0× 7 0.1× 55 0.7× 1 0.0× 23 416
Jin Zhu China 8 60 0.6× 38 0.4× 28 0.3× 18 0.7× 15 244
Kanta Naito Japan 10 131 1.2× 52 0.6× 20 0.2× 3 0.1× 51 278
Guillaume Bernard France 10 2 0.0× 15 0.2× 8 0.1× 15 0.2× 27 1.0× 31 318
Jiwei Zhang China 9 48 0.4× 32 0.4× 12 0.1× 2 0.1× 51 374
Matthias Schulte Germany 11 134 1.3× 29 0.3× 34 0.4× 1 0.0× 25 339
Georg Hahn United States 8 10 0.1× 86 1.0× 19 0.2× 2 0.1× 36 171
Homero Nogueira Guimarães Brazil 11 1 0.0× 10 0.1× 20 0.2× 40 0.5× 4 0.1× 30 354

Countries citing papers authored by Rajen D. Shah

Since Specialization
Citations

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

Fields of papers citing papers by Rajen D. Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rajen D. Shah. 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 Rajen D. Shah. The network helps show where Rajen D. Shah may publish in the future.

Co-authorship network of co-authors of Rajen D. Shah

This figure shows the co-authorship network connecting the top 25 collaborators of Rajen D. Shah. A scholar is included among the top collaborators of Rajen D. Shah 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 Rajen D. Shah. Rajen D. Shah 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.
Shah, Rajen D., et al.. (2024). The projected covariance measure for assumption-lean variable significance testing. The Annals of Statistics. 52(6). 2 indexed citations
2.
Shah, Rajen D., et al.. (2024). Sandwich boosting for accurate estimation in partially linear models for grouped data. Journal of the Royal Statistical Society Series B (Statistical Methodology). 86(5). 1286–1311.
3.
Wang, Yuhao & Rajen D. Shah. (2024). Debiased inverse propensity score weighting for estimation of average treatment effects with high-dimensional confounders. The Annals of Statistics. 52(5). 1 indexed citations
4.
Shah, Rajen D., et al.. (2024). Rank-transformed subsampling: inference for multiple data splitting and exchangeable p-values. Journal of the Royal Statistical Society Series B (Statistical Methodology). 87(1). 256–286. 4 indexed citations
5.
Jayaram, Satish Arcot, Tim J. Stevens, Nadine Muschalik, et al.. (2023). Functional unknomics: Systematic screening of conserved genes of unknown function. PLoS Biology. 21(8). e3002222–e3002222. 26 indexed citations
6.
Shah, Rajen D., et al.. (2022). Formulation, Device, and Clinical Factors Influencing the Targeted Delivery of COVID-19 Vaccines to the Lungs. AAPS PharmSciTech. 24(1). 2–2. 9 indexed citations
7.
Shah, Rajen D. & Peter Bühlmann. (2022). Double-Estimation-Friendly Inference for High-Dimensional Misspecified Models. Statistical Science. 38(1). 2 indexed citations
8.
Zhao, Qingyuan, et al.. (2021). BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic. The Annals of Applied Statistics. 15(1). 16 indexed citations
9.
Shah, Rajen D., et al.. (2020). Right Singular Vector Projection Graphs: Fast High Dimensional Covariance Matrix Estimation under Latent Confounding. Journal of the Royal Statistical Society Series B (Statistical Methodology). 82(2). 361–389. 9 indexed citations
10.
Mitchell, Piers D., Richard Brown, Tengyao Wang, et al.. (2019). Multicentre study of physical abuse and limb fractures in young children in the East Anglia Region, UK. Archives of Disease in Childhood. 104(10). 956–961. 3 indexed citations
11.
Shah, Rajen D. & Jonas Peters. (2019). The Hardness of Conditional Independence Testing and the Generalised Covariance Measure. Apollo (University of Cambridge). 89 indexed citations
12.
Shah, Rajen D.. (2016). Modelling interactions in high-dimensional data with backtracking. Journal of Machine Learning Research. 17(1). 7225–7255. 4 indexed citations
13.
Shah, Rajen D. & Richard J. Samworth. (2015). Comment. Journal of the American Statistical Association. 110(512). 1439–1442.
14.
Shah, Rajen D., et al.. (2015). Pharmacokinetic studies for proving bioequivalence of orally inhaled drug products—critical issues and concepts. Frontiers in Pharmacology. 6. 117–117. 7 indexed citations
15.
Shah, Rajen D. & Nicolai Meinshausen. (2014). Random intersection trees. Journal of Machine Learning Research. 15(1). 629–654. 13 indexed citations
16.
Shah, Rajen D., et al.. (2013). A COMPARATIVE DERMAL MICRODIALYSIS STUDY OF DICLOFENAC QPS VERSUS CONVENTIONAL 1% DICLOFENAC GEL. International Journal of Pharmaceutical Sciences and Drug Research. 175–178. 2 indexed citations
17.
Shah, Rajen D., et al.. (2011). COMPARATIVE BIOAVAILABILITY STUDY WITH TWO SODIUM VALPROATE TABLET FORMULATIONS IN HEALTHY SUBJECTS. International Journal of Pharmaceutical Sciences and Drug Research. 101–103. 1 indexed citations
18.
Iyer, Raman, et al.. (1996). Extrusion/Spheronization—Effect of Moisture Content and Spheronization Time on Pellet Characteristics. Pharmaceutical Development and Technology. 1(4). 325–331. 15 indexed citations
19.
20.
Shah, Rajen D., et al.. (1994). Physicomechanical Characterization of the Extrusion-Spheronization Process. I. Instrumentation of the Extruder. Pharmaceutical Research. 11(3). 355–360. 34 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Kamlesh Kumar Shukla Breakdown of academic impact, for papers by John Mack Breakdown of academic impact, for papers by Shlomo Reisner Breakdown of academic impact, for papers by Jin Zhu Breakdown of academic impact, for papers by Kanta Naito Breakdown of academic impact, for papers by Guillaume Bernard Breakdown of academic impact, for papers by Jiwei Zhang Breakdown of academic impact, for papers by Matthias Schulte Breakdown of academic impact, for papers by Georg Hahn Breakdown of academic impact, for papers by Homero Nogueira Guimarães
Rankless by CCL
2026