Faiz Currim

629 total citations
32 papers, 372 citations indexed

About

Faiz Currim is a scholar working on Artificial Intelligence, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Faiz Currim has authored 32 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 12 papers in Computer Networks and Communications and 8 papers in Signal Processing. Recurrent topics in Faiz Currim's work include Advanced Database Systems and Queries (11 papers), Semantic Web and Ontologies (10 papers) and Data Management and Algorithms (8 papers). Faiz Currim is often cited by papers focused on Advanced Database Systems and Queries (11 papers), Semantic Web and Ontologies (10 papers) and Data Management and Algorithms (8 papers). Faiz Currim collaborates with scholars based in United States, South Korea and Canada. Faiz Currim's co-authors include Sudha Ram, Karthik Srinivasan, Yun Wang, Richard T. Snodgrass, Curtis Dyreson, Kevin Kampschroer, Bijan Najafi, Judith Heerwagen, Hyoki Lee and Javad Razjouyan and has published in prestigious journals such as Communications of the ACM, Information Systems Research and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Faiz Currim

31 papers receiving 359 citations

Peers

Faiz Currim
Comparison fields: 5 of 99
  • Computer Networks and Communications 93
  • Artificial Intelligence 81
  • Building and Construction 79
  • Information Systems 52
  • Health, Toxicology and Mutagenesis 49
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Citations per field, relative to Faiz Currim
Faiz Currim · 1×
Citations per year, relative to Faiz Currim
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Countries citing papers authored by Faiz Currim

Since Specialization
Citations

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

Fields of papers citing papers by Faiz Currim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Faiz Currim. 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 Faiz Currim. The network helps show where Faiz Currim may publish in the future.

Co-authorship network of co-authors of Faiz Currim

This figure shows the co-authorship network connecting the top 25 collaborators of Faiz Currim. A scholar is included among the top collaborators of Faiz Currim 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 Faiz Currim. Faiz Currim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 6
2 0
3 3
4 22
5 3
6 1
7 55
8 73
9 21
10 2
11
Deep Learning for Bus Passenger Demand Prediction Using Big Data
4
12 25
13
Using Big Data for Predicting Freshmen Retention
8
14 7
15 4
16 19
17 5
18 5
19 4
20
Spatio-temporal set-based constraints in conceptual modeling: A theoretical framework and evaluation
2

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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