Paul Rad
- Signal Processing top 2%
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- IoT and Edge/Fog Computing 6
- Advanced Data Storage Technologies 5
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- Video Surveillance and Tracking Methods 7
- Advanced Neural Network Applications 5
- Face recognition and analysis 4
- Artificial Intelligence top 2%
- Information Systems top 2%
- Cloud Computing and Resource Management 9
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- Autonomous Vehicle Technology and Safety 5
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- EEG and Brain-Computer Interfaces 4
- Co-authors
- Kim‐Kwang Raymond ChooMehdi RoopaeiGonzalo De La Torre ParraMo JamshidiNicole BeebeGonzalo de la TorreJohn J. PrevostYufei Huang
- Cited by
- Signal ProcessingComputer Networks and CommunicationsComputer Vision and Pattern Recognition
- Journals
- Journal of Network and Computer Applications (2 papers)IEEE Access (2 papers)IEEE Transactions on Big Data (2 papers)
- Partner nations
- United StatesIranPoland
In The Last Decade
Paul Rad
66 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Signal Processing 311
- Computer Networks and Communications 526
- Computer Vision and Pattern Recognition 373
- Artificial Intelligence 480
- Information Systems 327
Countries citing papers authored by Paul Rad
This map shows the geographic impact of Paul Rad'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 Paul Rad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Rad more than expected).
Fields of papers citing papers by Paul Rad
This network shows the impact of papers produced by Paul Rad. 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 Paul Rad. The network helps show where Paul Rad may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Paul Rad, 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 | 2025 | 1 | |
| 2 | 2023 | 5 | |
| 3 | 2022 | 14 | |
| 4 | 2021 | 4 | |
| 5 | 2020 | 10 | |
| 6 | 2020 | 56 | |
| 7 | 2020 | 0 | |
| 8 | 2019 | 9 | |
| 9 | 2019 | 73 | |
| 10 | 2019 | 13 | |
| 11 | 2019 | 81 | |
| 12 | 2018 | 33 | |
| 13 | 2018 | 1 | |
| 14 | 2018 | 26 | |
| 15 | 2018 | 9 | |
| 16 | 2018 | 13 | |
| 17 | 2017 | 23 | |
| 18 | 2017 | 51 | |
| 19 | 2017 | 20 | |
| 20 | 2016 | 15 |
About Paul Rad
Paul Rad is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Information Systems, Signal Processing and Computer Networks and Communications, having authored 67 papers that have together received 1.7k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (9 papers), Video Surveillance and Tracking Methods (7 papers), IoT and Edge/Fog Computing (6 papers), Autonomous Vehicle Technology and Safety (5 papers), Advanced Neural Network Applications (5 papers), Advanced Data Storage Technologies (5 papers), Face recognition and analysis (4 papers) and EEG and Brain-Computer Interfaces (4 papers). The work is most often cited by research in Signal Processing (311 citations), Computer Networks and Communications (526 citations), Computer Vision and Pattern Recognition (373 citations), Artificial Intelligence (480 citations) and Information Systems (327 citations). Paul Rad has collaborated with scholars based in United States, Iran and Poland. Frequent co-authors include Kim‐Kwang Raymond Choo, Mehdi Roopaei, Gonzalo De La Torre Parra, Mo Jamshidi, Nicole Beebe, Gonzalo de la Torre, John J. Prevost, Yufei Huang, Patrick Benavidez and Arun Das. Their work appears in journals such as Journal of Network and Computer Applications, IEEE Access, IEEE Transactions on Big Data, Future Generation Computer Systems and Information Systems Frontiers.
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.