John Paparrizos
- Signal Processing top 0.5%
- Artificial Intelligence top 1%
- Computer Networks and Communications top 5%
- Economics and Econometrics top 5%
- Electrical and Electronic Engineering
- Co-authors
- Luis GravanoMichael J. FranklinPaul BoniolThemis PalpanasAaron J. ElmoreChunwei LiuEric HorvitzRyen W. White
- Topics
- Time Series Analysis and Forecasting (29 papers)Anomaly Detection Techniques and Applications (22 papers)Complex Systems and Time Series Analysis (9 papers)
- Partner nations
- United StatesFranceGreece
In The Last Decade
John Paparrizos
42 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Signal Processing 893
- Artificial Intelligence 891
- Computer Networks and Communications 290
- Economics and Econometrics 233
- Electrical and Electronic Engineering 121
Countries citing papers authored by John Paparrizos
This map shows the geographic impact of John Paparrizos'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 John Paparrizos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Paparrizos more than expected).
Fields of papers citing papers by John Paparrizos
This network shows the impact of papers produced by John Paparrizos. 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 John Paparrizos. The network helps show where John Paparrizos may publish in the future.
Co-authorship network of co-authors of John Paparrizos
This figure shows the co-authorship network connecting the top 25 collaborators of John Paparrizos. A scholar is included among the top collaborators of John Paparrizos 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 John Paparrizos. John Paparrizos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 3 | |
| 3 | 6 | |
| 4 | 3 | |
| 5 | 6 | |
| 6 | 10 | |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 7 | |
| 10 | 13 | |
| 11 | 6 | |
| 12 | 3 | |
| 13 | 3 | |
| 14 | 7 | |
| 15 | 9 | |
| 16 | 15 | |
| 17 | VergeDB: A Database for IoT Analytics on Edge Devices. | 19 |
| 18 | 16 | |
| 19 | 136 | |
| 20 | k-Shapebreakdown → | 411 |
About John Paparrizos
John Paparrizos is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 44 papers that have together received 1.5k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (29 papers), Anomaly Detection Techniques and Applications (22 papers) and Complex Systems and Time Series Analysis (9 papers). The work is most often cited by research in Signal Processing (893 citations), Artificial Intelligence (891 citations) and Computer Networks and Communications (290 citations). John Paparrizos has collaborated with scholars based in United States, France and Greece. Frequent co-authors include Luis Gravano, Michael J. Franklin, Paul Boniol, Themis Palpanas, Aaron J. Elmore, Chunwei Liu, Eric Horvitz, Ryen W. White, Ruey S. Tsay and Hao Jiang. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGMOD Record and ACM Transactions on Database 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.