Rahul Shah

1.7k citations
53 papers · 692 indexed · h-index 13
Topics
Algorithms and Data Compression (38 papers)DNA and Biological Computing (17 papers)Network Packet Processing and Optimization (15 papers)

In The Last Decade

Rahul Shah

50 papers receiving 643 citations

Peers

Rahul Shah
Comparison fields: 5 of 36
  • Artificial Intelligence 428
  • Signal Processing 380
  • Computer Networks and Communications 316
  • Molecular Biology 128
  • Information Systems 124
Replace Vo Ngoc Anh with:
Vo Ngoc Anh Australia
Seung-won Hwang South Korea
Walter A. Burkhard United States
Makoto Onizuka Japan
Rudolf Bayer Germany
Jeffrey Jestes United States
Yuan‐Chi Chang United States
Xiangye Xiao Hong Kong
Gabriel M. Kuper United States
Niels Nes Netherlands
Rahul Shah relative to Vo Ngoc Anh Australia Vo Ngoc Anh's profile →
Citations per field
00.5×1.5×
Vo Ngoc Anh · 1×
Citations per year

Countries citing papers authored by Rahul Shah

Since Specialization
Citations

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

Fields of papers citing papers by Rahul Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rahul Shah

This figure shows the co-authorship network connecting the top 25 collaborators of Rahul Shah. A scholar is included among the top collaborators of Rahul 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 Rahul Shah. Rahul 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
#WorkIndexed citations
1 4
2 6
3 8
4 5
5 5
6 5
7 7
8 2
9 9
10 3
11 4
12 12
13 1
14 36
15
The Orion Uncertain Data Management System
5
16
Indexing Probabilistic Nearest-Neighbor Threshold Queries.
4
17 66
18 36
19
Dynamic Rank/Select Dictionaries with Applications to XML Indexing
3
20 9

About Rahul Shah

Rahul Shah is a scholar working on Hardware and Architecture, Artificial Intelligence and Signal Processing, having authored 53 papers that have together received 692 indexed citations. Recurring topics across this work include Algorithms and Data Compression (38 papers), DNA and Biological Computing (17 papers) and Network Packet Processing and Optimization (15 papers). The work is most often cited by research in Signal Processing (380 citations), Computer Networks and Communications (316 citations) and Artificial Intelligence (428 citations). Rahul Shah has collaborated with scholars based in United States, Taiwan and Hong Kong. Frequent co-authors include Jeffrey Scott Vitter, Wing-Kai Hon, Sunil Prabhakar, Sarvjeet Singh, Chris Mayfield, Susanne E. Hambrusch, Walid G. Aref, Reynold Cheng, Sharma V. Thankachan and Ihab F. Ilyas. Their work appears in journals such as Journal of the ACM, BMC Genomics and Theoretical Computer Science.

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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