Aneesh Sharma

2.1k citations
27 papers · 1.1k · h-index 12

Impact in

Papers in

Aneesh Sharma

26 papers receiving 1.1k citations

Peers

Aneesh Sharma
Comparison fields: 5 of 88
  • Statistical and Nonlinear Physics 401
  • Information Systems 429
  • Signal Processing 180
  • Communication 96
  • Computer Vision and Pattern Recognition 280
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Sancheng Peng China
Jafar Adibi United States
Xiangyang Lan United States
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Citations per field
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Citations per year

Countries citing papers authored by Aneesh Sharma

Since Specialization
Citations

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

Fields of papers citing papers by Aneesh Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Aneesh Sharma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Aneesh Sharma Line = papers co-authored together Aneesh Sharma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013280
2 2009257
3 2014202
4 201563
5 201360
6 201653
7 201652
8 202023
9 201521
10 201319
11
Discovering Similar Users on Twitter
201317
12 201313
13 20119
14 20206
15 20045
16
An Axiomatic Framework for Result Diversification
20094
17
Centralized data recording for a distributed surgical skills trainer to facilitate automated proficiency evaluation.
20074
18 20154
19 20113
20 20212

About Aneesh Sharma

Aneesh Sharma is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Artificial Intelligence, Computer Networks and Communications and Information Systems, having authored 27 papers that have together received 1.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (9 papers), Advanced Graph Neural Networks (5 papers), Robotic Path Planning Algorithms (5 papers), Opinion Dynamics and Social Influence (5 papers), Data Management and Algorithms (2 papers), Optimization and Search Problems (2 papers), Caching and Content Delivery (2 papers) and Social Media and Politics (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (401 citations), Information Systems (429 citations), Signal Processing (180 citations), Communication (96 citations) and Computer Vision and Pattern Recognition (280 citations). Aneesh Sharma has collaborated with scholars based in United States, India and Taiwan. Frequent co-authors include Sreenivas Gollapudi, Jimmy Lin, Pankaj Gupta, Reza Bosagh Zadeh, Seth A. Myers, Dong Wang, Ashish Goel, Ashish Goel, Sharad Goel and Jessica Lasky‐Su. Their work appears in journals such as Proceedings of the VLDB Endowment, Journal of Dynamic Systems Measurement and Control, Indian Journal of Science and Technology, SIAM Journal on Discrete Mathematics and Proceedings of the National Academy of Sciences.

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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