Navin Kabra
Impact in
- Signal Processing top 2%
- Data Management and Algorithms
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- Advanced Database Systems and Queries
- Advanced Data Storage Technologies
- Distributed systems and fault tolerance
Papers in
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- Advanced Database Systems and Queries 7
- Advanced Data Storage Technologies 2
- Peer-to-Peer Network Technologies 2
- Distributed systems and fault tolerance 1
- Optimization and Search Problems 1
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- Data Management and Algorithms 7
- Co-authors
- David J. DeWitt (5 shared papers)Jignesh M. Patel (3 shared papers)Jun Luo (1 shared paper)Josef Burger (2 shared papers)Karthikeyan Ramasamy (2 shared papers)Jeffrey F. Naughton (2 shared papers)Roger Lueder (2 shared papers)Curt J. Ellmann (2 shared papers)
- Journals
- ACM SIGMOD Record (2 papers)The VLDB Journal (1 paper)Very Large Data Bases (1 paper)
- Partner nations
- United StatesFrance
In The Last Decade
Navin Kabra
8 papers receiving 447 citations
Peers
Comparison fields: 5 of 27
- Signal Processing 382
- Computer Networks and Communications 444
- Geography, Planning and Development 38
- Information Systems 137
- Artificial Intelligence 139
Countries citing papers authored by Navin Kabra
This map shows the geographic impact of Navin Kabra'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 Navin Kabra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Navin Kabra more than expected).
Fields of papers citing papers by Navin Kabra
This network shows the impact of papers produced by Navin Kabra. 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 Navin Kabra. The network helps show where Navin Kabra may publish in the future.
Co-authors
The 13 scholars most cited alongside Navin Kabra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1998 | 223 | |
| 2 | Client-Server Paradise | 1994 | 99 |
| 3 | 1997 | 73 | |
| 4 | 1998 | 52 | |
| 5 | 1999 | 23 | |
| 6 | 1997 | 21 | |
| 7 | 2004 | 8 | |
| 8 | 2004 | 1 | |
| 9 | Query optimization for object-relational database systems | 1999 | 0 |
About Navin Kabra
Navin Kabra is a scholar working on Computer Networks and Communications, Signal Processing, Information Systems, Geography, Planning and Development and Infectious Diseases, having authored 9 papers that have together received 500 indexed citations. Recurring topics across this work include Data Management and Algorithms (7 papers), Advanced Database Systems and Queries (7 papers), Geographic Information Systems Studies (3 papers), Advanced Data Storage Technologies (2 papers), Cloud Computing and Resource Management (2 papers), Peer-to-Peer Network Technologies (2 papers), Distributed systems and fault tolerance (1 paper) and Optimization and Search Problems (1 paper). The work is most often cited by research in Signal Processing (382 citations), Computer Networks and Communications (444 citations), Geography, Planning and Development (38 citations), Information Systems (137 citations) and Artificial Intelligence (139 citations). Navin Kabra has collaborated with scholars based in United States and France. Frequent co-authors include David J. DeWitt, Jignesh M. Patel, Jun Luo, Josef Burger, Karthikeyan Ramasamy, Jeffrey F. Naughton, Roger Lueder, Curt J. Ellmann, Kristin Tufte and Raghu Ramakrishnan. Their work appears in journals such as ACM SIGMOD Record, The VLDB Journal and Very Large Data Bases.
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.