Sunil Prabhakar

124 papers receiving 4.1k citations

Sunil Prabhakar's Hit Papers

Evaluating probabilistic queries over imprecise data 2003 · 469 citations
4690+7+15Years since publication100200300400

Peers

Sunil Prabhakar
Comparison fields: 5 of 85
  • Signal Processing 2.7k
  • Geography, Planning and Development 573
  • Computer Networks and Communications 2.2k
  • Artificial Intelligence 1.6k
  • Computer Vision and Pattern Recognition 958
Replace Yunjun Gao with:
Yunjun Gao China
Vassilis J. Tsotras United States
Marios Hadjieleftheriou United States
Nick Roussopoulos United States
Ke Yi Hong Kong
Man Lung Yiu Hong Kong
Flip Korn United States
Dmitri V. Kalashnikov United States
Nilesh Dalvi United States
Shuo Shang China
Sunil Prabhakar relative to Yunjun Gao China Yunjun Gao's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sunil Prabhakar

Since Specialization
Citations

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

Fields of papers citing papers by Sunil Prabhakar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sunil Prabhakar, 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 Sunil Prabhakar Line = papers co-authored together Sunil Prabhakar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 130 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Evaluating probabilistic queries over imprecise data
Hit paper breakdown →
2003469
2 2004333
3 2002270
4 2006268
5
Indexing multi-dimensional uncertain data with arbitrary probability density functions
2005223
6 2004212
7 2004157
8 2010133
9 2007103
10 200996
11 200490
12 200386
13 200879
14
U-DBMS: a database system for managing constantly-evolving data
200577
15 200876
16 200673
17 200272
18 200669
19 200558
20 200356

About Sunil Prabhakar

Sunil Prabhakar is a scholar working on Computer Networks and Communications, Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 130 papers that have together received 4.3k indexed citations. Recurring topics across this work include Data Management and Algorithms (62 papers), Advanced Database Systems and Queries (47 papers), Algorithms and Data Compression (14 papers), Advanced Data Storage Technologies (14 papers), Advanced Steganography and Watermarking Techniques (13 papers), Data Mining Algorithms and Applications (13 papers), Cryptography and Data Security (10 papers) and Advanced Image and Video Retrieval Techniques (10 papers). The work is most often cited by research in Signal Processing (2.7k citations), Geography, Planning and Development (573 citations), Computer Networks and Communications (2.2k citations), Artificial Intelligence (1.6k citations) and Computer Vision and Pattern Recognition (958 citations). Sunil Prabhakar has collaborated with scholars based in United States, Hong Kong and India. Frequent co-authors include Reynold Cheng, Dmitri V. Kalashnikov, Susanne E. Hambrusch, Mikhail J. Atallah, Yuni Xia, Radu Sion, Sarvjeet Singh, Chris Mayfield, Walid G. Aref and Elisa Bertino. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Information Systems, Distributed and Parallel Databases, Multimedia Systems and Knowledge and Information Systems.

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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