Peter Boncz
About
In The Last Decade
Peter Boncz
120 papers receiving 4.0k citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Computer Networks and Communications 3.6k
- Artificial Intelligence 1.8k
- Signal Processing 1.7k
- Information Systems 1.4k
- Computer Vision and Pattern Recognition 902
Countries citing papers authored by Peter Boncz
This map shows the geographic impact of Peter Boncz'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 Peter Boncz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Boncz more than expected).
Fields of papers citing papers by Peter Boncz
This network shows the impact of papers produced by Peter Boncz. 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 Peter Boncz. The network helps show where Peter Boncz may publish in the future.
Co-authorship network of co-authors of Peter Boncz
This figure shows the co-authorship network connecting the top 25 collaborators of Peter Boncz. A scholar is included among the top collaborators of Peter Boncz 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 Peter Boncz. Peter Boncz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 9 | |
| 5 | Highlighting the Performance Diversity of Analytical Queries using VOILA. | 1 |
| 6 | White-box compression: Learning and exploiting compact table representations | 6 |
| 7 | Optimizing group-by and aggregation using GPU-CPU co-processing | 3 |
| 8 | Learned Cardinalities: Estimating Correlated Joins with Deep Learning | 14 |
| 9 | Linked Stream Data Processing: Facts and Figures | 1 |
| 10 | SciBORQ: Scientific Data Management with Bounds on Runtime and Quality | 54 |
| 11 | Cooperative scans: dynamic bandwidth sharing in a DBMS | 80 |
| 12 | XRPC: interoperable and efficient distributed XQuery | 18 |
| 13 | Efficient and Flexible Information Retrieval Using MonetDB/X100 | 7 |
| 14 | Efficient XQuery Support for Stand-Off Annotation | 7 |
| 15 | MonetDB/X100 - A DBMS in the CPU cache | 79 |
| 16 | 21 | |
| 17 | MonetDB/X100: Hyper-Pipelining Query Execution | 334 |
| 18 | AmbientDB: P2P Database Technology for Ambient Intelligent Multimedia Applications | 1 |
| 19 | Monet; a next-Generation DBMS Kernel For Query-Intensive Applications | 102 |
| 20 | High performance support for OO traversals in Monet | 9 |
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.