Georgios Kellaris
Impact in
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- Mobile Crowdsensing and Crowdsourcing
- Artificial Intelligence top 5%
- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Internet Traffic Analysis and Secure E-voting
Papers in
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- Privacy-Preserving Technologies in Data 5
- Cryptography and Data Security 5
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- Cloud Data Security Solutions 1
- Co-authors
- Stavros Papadopoulos (2 shared papers)Kobbi Nissim (3 shared papers)George Kollios (3 shared papers)Adam O’Neill (2 shared papers)Dimitris Papadias (1 shared paper)Xiaokui Xiao (1 shared paper)Nikos Pelekis (1 shared paper)Yannis Theodoridis (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (4 papers)Journal of Systems and Software (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesHong KongSingapore
In The Last Decade
Georgios Kellaris
7 papers receiving 449 citations
Peers
Comparison fields: 5 of 31
- Computer Science Applications 81
- Artificial Intelligence 379
- Signal Processing 77
- Transportation 47
- Computer Networks and Communications 85
Countries citing papers authored by Georgios Kellaris
This map shows the geographic impact of Georgios Kellaris'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 Georgios Kellaris with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Georgios Kellaris more than expected).
Fields of papers citing papers by Georgios Kellaris
This network shows the impact of papers produced by Georgios Kellaris. 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 Georgios Kellaris. The network helps show where Georgios Kellaris may publish in the future.
Co-authors
The 10 scholars most cited alongside Georgios Kellaris, 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 | 2014 | 157 | |
| 2 | 2016 | 156 | |
| 3 | 2013 | 64 | |
| 4 | 2013 | 47 | |
| 5 | 2010 | 23 | |
| 6 | 2021 | 7 | |
| 7 | 2023 | 5 |
About Georgios Kellaris
Georgios Kellaris is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Computer Networks and Communications and Sociology and Political Science, having authored 7 papers that have together received 459 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (5 papers), Cryptography and Data Security (5 papers), Data Management and Algorithms (2 papers), Cloud Data Security Solutions (1 paper), Automated Road and Building Extraction (1 paper), Mobile Crowdsensing and Crowdsourcing (1 paper), Opportunistic and Delay-Tolerant Networks (1 paper) and Vehicular Ad Hoc Networks (VANETs) (1 paper). The work is most often cited by research in Computer Science Applications (81 citations), Artificial Intelligence (379 citations), Signal Processing (77 citations), Transportation (47 citations) and Computer Networks and Communications (85 citations). Georgios Kellaris has collaborated with scholars based in United States, Hong Kong and Singapore. Frequent co-authors include Stavros Papadopoulos, Kobbi Nissim, George Kollios, Adam O’Neill, Dimitris Papadias, Xiaokui Xiao, Nikos Pelekis, Yannis Theodoridis, Kyriakos Mouratidis and Nikos Mamoulis. Their work appears in journals such as Proceedings of the VLDB Endowment, Journal of Systems and Software and arXiv (Cornell University).
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.