Joe Hellerstein
Impact in
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- Advanced Database Systems and Queries
- Energy Efficient Wireless Sensor Networks
- Advanced Data Storage Technologies
- Peer-to-Peer Network Technologies
- Distributed systems and fault tolerance
- Signal Processing top 10%
- Data Management and Algorithms
Papers in
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- Advanced Database Systems and Queries 3
- Software-Defined Networks and 5G 1
- Distributed and Parallel Computing Systems 1
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- Cloud Computing and Resource Management 1
- Co-authors
- Samuel Madden (1 shared paper)Michael Stonebraker (5 shared papers)Jeff Naughton (1 shared paper)David J. DeWitt (1 shared paper)Michael L. Brodie (1 shared paper)H. V. Jagadish (1 shared paper)Phil Bernstein (1 shared paper)Jim Gray (1 shared paper)
- Journals
- ACM SIGMOD Record (1 paper)Morgan Kaufmann Publishers Inc. eBooks (4 papers)
- Partner nations
- United States
In The Last Decade
Joe Hellerstein
9 papers receiving 180 citations
Peers
Comparison fields: 5 of 69
- Computer Networks and Communications 159
- Signal Processing 62
- Information Systems 70
- Artificial Intelligence 52
- Hardware and Architecture 8
Countries citing papers authored by Joe Hellerstein
This map shows the geographic impact of Joe Hellerstein'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 Joe Hellerstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joe Hellerstein more than expected).
Fields of papers citing papers by Joe Hellerstein
This network shows the impact of papers produced by Joe Hellerstein. 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 Joe Hellerstein. The network helps show where Joe Hellerstein may publish in the future.
Co-authors
The 17 scholars most cited alongside Joe Hellerstein, 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 | 138 | |
| 2 | TinyDB: In-Network Query Processing in TinyOS | 2002 | 40 |
| 3 | The roots | 1998 | 23 |
| 4 | Using mobile technology and social networking to crowdsource citizen science | 2012 | 11 |
| 5 | Benchmarking database systems | 1998 | 2 |
| 6 | Distributed database systems | 1998 | 1 |
| 7 | Parallel database systems | 1998 | 1 |
| 8 | 1998 | 1 | |
| 9 | 2013 | 1 |
About Joe Hellerstein
Joe Hellerstein is a scholar working on Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition, Information Systems and Management and Ecological Modeling, having authored 9 papers that have together received 218 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (3 papers), Graph Theory and Algorithms (1 paper), Species Distribution and Climate Change (1 paper), Software-Defined Networks and 5G (1 paper), Cloud Computing and Resource Management (1 paper), Scientific Computing and Data Management (1 paper), Distributed and Parallel Computing Systems (1 paper) and Data Quality and Management (1 paper). The work is most often cited by research in Computer Networks and Communications (159 citations), Signal Processing (62 citations), Information Systems (70 citations), Artificial Intelligence (52 citations) and Hardware and Architecture (8 citations). Joe Hellerstein has collaborated with scholars based in United States. Frequent co-authors include Samuel Madden, Michael Stonebraker, Jeff Naughton, David J. DeWitt, Michael L. Brodie, H. V. Jagadish, Phil Bernstein, Jim Gray, Stefano Ceri and Hamid Pirahesh. Their work appears in journals such as ACM SIGMOD Record and Morgan Kaufmann Publishers Inc. eBooks.
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.