Sharad Mehrotra

17.8k citations
253 papers · 10.1k indexed · 5 hit papers · h-index 41

Sharad Mehrotra

241 papers receiving 9.3k citations

Hit Papers

Relevance feedback: a power tool for interactive content-...1998202620072016199820012002200120022505007501000

Peers

Sharad Mehrotra
Comparison fields: 5 of 144
  • Computer Vision and Pattern Recognition 4.0k
  • Artificial Intelligence 3.9k
  • Signal Processing 3.5k
  • Computer Networks and Communications 2.4k
  • Information Systems 2.1k
Replace Dimitrios Gunopulos with:
Dimitrios Gunopulos United States
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Citations per field
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Citations per year

Countries citing papers authored by Sharad Mehrotra

Since Specialization
Citations

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

Fields of papers citing papers by Sharad Mehrotra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sharad Mehrotra

This figure shows the co-authorship network connecting the top 25 collaborators of Sharad Mehrotra. A scholar is included among the top collaborators of Sharad Mehrotra 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 Sharad Mehrotra. Sharad Mehrotra 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 0
2 3
3 8
4
Secure Data Processing over Hybrid Clouds.
6
5
Community Driven Data Integration for Emergency Response
1
6 5
7 15
8
Fault-Tolerant Queries over Sensor Data
2
9 117
10 22
11 1
12
Integrating similarity based retrieval and query refinement in databases
9
13 7
14
Query Refinement in Similarity Retrieval Systems.
3
15
Dimensionality Reduction for Fast Similarity Search in Large Time Series Databasesbreakdown →
1003
16
Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces
163
17
Information Retrieval beyond the Text Document
4
18 15
19 80
20
Transcending the Serializability Requirement.
2

About Sharad Mehrotra

Sharad Mehrotra is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 253 papers that have together received 10.1k indexed citations. Recurring topics across this work include Data Management and Algorithms (60 papers), Advanced Database Systems and Queries (43 papers) and Privacy-Preserving Technologies in Data (39 papers). The work is most often cited by research in Signal Processing (3.5k citations), Computer Vision and Pattern Recognition (4.0k citations) and Artificial Intelligence (3.9k citations). Sharad Mehrotra has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Kaushik Chakrabarti, Thomas S. Huang, Yong Rui, Eamonn Keogh, Michael J. Pazzani, M. Ortega, Hakan Hacígümüş, B. R. Iyer, Chen Li and Dmitri V. Kalashnikov. Their work appears in journals such as Communications of the ACM, IEEE Transactions on Image Processing and IEEE Transactions on Knowledge and Data Engineering.

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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