Nihar B. Shah

4.0k total citations
79 papers, 1.7k citations indexed

About

Nihar B. Shah is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Nihar B. Shah has authored 79 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 28 papers in Computer Networks and Communications and 20 papers in Information Systems. Recurrent topics in Nihar B. Shah's work include Advanced Data Storage Technologies (24 papers), Caching and Content Delivery (22 papers) and Mobile Crowdsensing and Crowdsourcing (17 papers). Nihar B. Shah is often cited by papers focused on Advanced Data Storage Technologies (24 papers), Caching and Content Delivery (22 papers) and Mobile Crowdsensing and Crowdsourcing (17 papers). Nihar B. Shah collaborates with scholars based in United States, India and Russia. Nihar B. Shah's co-authors include Kannan Ramchandran, K. V. Rashmi, P. Vijay Kumar, Kangwook Lee, Dengyong Zhou, Dhruba Borthakur, Hairong Kuang, Martin J. Wainwright, Preetum Nakkiran and Christian Catalini and has published in prestigious journals such as PLoS ONE, Management Science and IEEE Transactions on Information Theory.

In The Last Decade

Nihar B. Shah

72 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nihar B. Shah United States 20 1.3k 504 347 233 138 79 1.7k
Luca Becchetti Italy 18 517 0.4× 525 1.0× 597 1.7× 121 0.5× 184 1.3× 60 1.5k
Paraschos Koutris United States 17 567 0.4× 534 1.1× 278 0.8× 172 0.7× 86 0.6× 64 1.1k
Spiros Skiadopoulos Greece 21 711 0.6× 855 1.7× 476 1.4× 72 0.3× 85 0.6× 58 1.7k
Gagan Aggarwal United States 15 303 0.2× 537 1.1× 151 0.4× 119 0.5× 63 0.5× 32 1.2k
Barzan Mozafari United States 21 1.0k 0.8× 671 1.3× 571 1.6× 71 0.3× 104 0.8× 49 1.6k
Aleksandrs Slivkins United States 24 865 0.7× 516 1.0× 135 0.4× 172 0.7× 176 1.3× 78 1.7k
Sreenivas Gollapudi United States 19 433 0.3× 748 1.5× 811 2.3× 118 0.5× 105 0.8× 76 1.9k
Erik Vee United States 19 539 0.4× 404 0.8× 190 0.5× 126 0.5× 13 0.1× 35 954
Stefano Bistarelli Italy 17 772 0.6× 783 1.6× 473 1.4× 265 1.1× 9 0.1× 133 1.5k
R.J. Lipton United States 19 562 0.4× 664 1.3× 878 2.5× 441 1.9× 51 0.4× 50 2.5k

Countries citing papers authored by Nihar B. Shah

Since Specialization
Citations

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

Fields of papers citing papers by Nihar B. Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nihar B. Shah

This figure shows the co-authorship network connecting the top 25 collaborators of Nihar B. Shah. A scholar is included among the top collaborators of Nihar B. 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 Nihar B. Shah. Nihar B. 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.
Lakkaraju, Himabindu, et al.. (2025). Detecting LLM-generated peer reviews. PLoS ONE. 20(9). e0331871–e0331871.
2.
Conitzer, Vincent, et al.. (2024). Testing for reviewer anchoring in peer review: A randomized controlled trial. PLoS ONE. 19(11). e0301111–e0301111.
3.
Beygelzimer, Alina, Yann Dauphin, Percy Liang, et al.. (2024). How do authors’ perceptions of their papers compare with co-authors’ perceptions and peer-review decisions?. PLoS ONE. 19(4). e0300710–e0300710.
4.
Chawla, Shuchi, et al.. (2023). Cite-seeing and reviewing: A study on citation bias in peer review. PLoS ONE. 18(7). e0283980–e0283980. 6 indexed citations
5.
Shah, Nihar B., et al.. (2023). Trends in research productivity of medical students matching to surgical subspecialties within North America: a bibliometric analysis. Global Surgical Education - Journal of the Association for Surgical Education. 2(1). 2 indexed citations
6.
Shah, Nihar B., et al.. (2023). A large scale randomized controlled trial on herding in peer-review discussions. PLoS ONE. 18(7). e0287443–e0287443. 5 indexed citations
7.
Shah, Nihar B., et al.. (2020). Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments. Neural Information Processing Systems. 33. 12533–12545. 6 indexed citations
8.
Shah, Nihar B., et al.. (2019). Your 2 is My 1, Your 3 is My 9: Handling Arbitrary Miscalibrations in Ratings. arXiv (Cornell University). 864–872. 8 indexed citations
9.
Noothigattu, Ritesh, Nihar B. Shah, & Ariel D. Procaccia. (2018). Choosing How to Choose Papers. arXiv (Cornell University). 1 indexed citations
10.
Heckel, Reinhard, Nihar B. Shah, Kannan Ramchandran, & Martin J. Wainwright. (2016). Active Ranking from Pairwise Comparisons and the Futility of Parametric Assumptions.. arXiv (Cornell University). 2 indexed citations
11.
Shah, Nihar B. & Dengyong Zhou. (2016). No oops, you won't do it again: mechanisms for self-correction in crowdsourcing. International Conference on Machine Learning. 1–10. 12 indexed citations
12.
Rashmi, K. V., et al.. (2015). Having your cake and eating it too: jointly optimal erasure codes for I/O, storage and network-bandwidth. File and Storage Technologies. 81–94. 92 indexed citations
13.
Shah, Nihar B. & Martin J. Wainwright. (2015). Simple, Robust and Optimal Ranking from Pairwise Comparisons. Journal of Machine Learning Research. 18(199). 1–38. 20 indexed citations
14.
Shah, Nihar B. & Dengyong Zhou. (2014). Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing. arXiv (Cornell University). 28. 1–9. 49 indexed citations
15.
Shah, Nihar B., K. V. Rashmi, & Kannan Ramchandran. (2014). One extra bit of download ensures perfectly private information retrieval. 856–860. 118 indexed citations
16.
Shah, Nihar B., Kangwook Lee, & Kannan Ramchandran. (2012). The MDS Queue. arXiv (Cornell University). 4 indexed citations
17.
Shah, Nihar B., Kangwook Lee, & Kannan Ramchandran. (2012). The MDS Queue: Analysing Latency Performance of Codes and Redundant Requests. arXiv (Cornell University). 17 indexed citations
18.
Shah, Nihar B., K. V. Rashmi, & Kannan Ramchandran. (2012). Secret Share Dissemination across a Network. arXiv (Cornell University). 1 indexed citations
19.
Rashmi, K. V., Nihar B. Shah, P. Vijay Kumar, & Kannan Ramchandran. (2009). Explicit construction of optimal exact regenerating codes for distributed storage. 1243–1249. 159 indexed citations
20.
Shah, Nihar B.. (2004). Using Distributed Computing To Improve The Performance Of Genetic Algorithms For Job Shop Scheduling Problems. OhioLink ETD Center (Ohio Library and Information Network). 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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