F. J. Burkowski

693 citations
46 papers · 450 indexed · h-index 11

F. J. Burkowski

40 papers receiving 367 citations

Peers

F. J. Burkowski
Comparison fields: 5 of 72
  • Signal Processing 104
  • Computer Networks and Communications 160
  • Artificial Intelligence 203
  • Information Systems 122
  • Numerical Analysis 29
Replace Robert L. Ashenhurst with:
Robert L. Ashenhurst United States
David Jordan United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by F. J. Burkowski

Since Specialization
Citations

This map shows the geographic impact of F. J. Burkowski'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 F. J. Burkowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites F. J. Burkowski more than expected).

Fields of papers citing papers by F. J. Burkowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by F. J. Burkowski. 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 F. J. Burkowski. The network helps show where F. J. Burkowski may publish in the future.

Co-authorship network

The 11 scholars most cited alongside F. J. Burkowski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with F. J. Burkowski Line = papers co-authored together F. J. Burkowski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20145
3 201114
4 200941
5 20093
6 20041
7 20024
8 199821
9
Delivery of Electronic News.
19955
10
Shortest substring ranking (MultiText experiments for TREC-4)
199543
11
Delivery of electronic news: a broadband application
19945
12 199235
13 199225
14
The use of retrieval filters to localize information in hierarchically tagged text-dominated database.
19912
15 19893
16 198110
17 19775
18 19732
19 197113
20 19717

About F. J. Burkowski

F. J. Burkowski is a scholar working on Hardware and Architecture, Numerical Analysis, Computer Networks and Communications, Computational Theory and Mathematics and Applied Mathematics, having authored 46 papers that have together received 450 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (7 papers), Advanced Database Systems and Queries (7 papers), Embedded Systems Design Techniques (6 papers), Algorithms and Data Compression (6 papers), Differential Equations and Numerical Methods (5 papers), Computational Drug Discovery Methods (5 papers), Distributed and Parallel Computing Systems (5 papers) and Advanced Data Storage Technologies (5 papers). The work is most often cited by research in Signal Processing (104 citations), Computer Networks and Communications (160 citations), Artificial Intelligence (203 citations), Information Systems (122 citations) and Numerical Analysis (29 citations). F. J. Burkowski has collaborated with scholars based in Canada and Hong Kong. Frequent co-authors include Gordon V. Cormack, William Wong, Michael Shepherd, Carolyn Watters, Charles L. A. Clarke, Laleh Soltan Ghoraie, Mu Zhu, W. D. Hoskins, Shuai Cheng Li and Henry Wolkowicz. Their work appears in journals such as INFORMS journal on computing, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Parallel Computing, SIAM Journal on Numerical Analysis and Bioinformatics.

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.

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