Read Sprabery
Impact in
- Software top 5%
- Software Testing and Debugging Techniques
- Signal Processing top 5%
- Advanced Malware Detection Techniques
Papers in
-
- Security and Verification in Computing 11
-
- Cloud Data Security Solutions 5
- Information and Cyber Security 1
- Co-authors
- Roy H. Campbell (8 shared papers)Bhargava Gopireddy (3 shared papers)Mengjia Yan (3 shared papers)Josep Torrellas (3 shared papers)Christopher W. Fletcher (3 shared papers)László Szekeres (1 shared paper)Masooda Bashir (3 shared papers)Kevin Kwiat (3 shared papers)
- Journals
- IEEE Micro (1 paper)Rose-Hulman Scholar (Rose–Hulman Institute of Technology) (2 papers)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Read Sprabery
13 papers receiving 331 citations
Peers
Comparison fields: 5 of 32
- Software 84
- Signal Processing 132
- Hardware and Architecture 81
- Information Systems 146
- Artificial Intelligence 202
Countries citing papers authored by Read Sprabery
This map shows the geographic impact of Read Sprabery'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 Read Sprabery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Read Sprabery more than expected).
Fields of papers citing papers by Read Sprabery
This network shows the impact of papers produced by Read Sprabery. 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 Read Sprabery. The network helps show where Read Sprabery may publish in the future.
Co-authors
The 23 scholars most cited alongside Read Sprabery, 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 | 2019 | 113 | |
| 2 | 2021 | 107 | |
| 3 | 2019 | 31 | |
| 4 | 2017 | 26 | |
| 5 | 2017 | 13 | |
| 6 | 2014 | 12 | |
| 7 | 2014 | 12 | |
| 8 | 2020 | 10 | |
| 9 | 2018 | 8 | |
| 10 | 2017 | 8 | |
| 11 | 2013 | 6 | |
| 12 | 2020 | 2 | |
| 13 | 2017 | 1 | |
| 14 | 2017 | 0 |
About Read Sprabery
Read Sprabery is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 14 papers that have together received 349 indexed citations. Recurring topics across this work include Security and Verification in Computing (11 papers), Advanced Malware Detection Techniques (6 papers), Cloud Data Security Solutions (5 papers), Network Security and Intrusion Detection (3 papers), Advanced Memory and Neural Computing (2 papers), Access Control and Trust (1 paper), Innovative Teaching Methods (1 paper) and Information and Cyber Security (1 paper). The work is most often cited by research in Software (84 citations), Signal Processing (132 citations), Hardware and Architecture (81 citations), Information Systems (146 citations) and Artificial Intelligence (202 citations). Read Sprabery has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Roy H. Campbell, Bhargava Gopireddy, Mengjia Yan, Josep Torrellas, Christopher W. Fletcher, László Szekeres, Masooda Bashir, Kevin Kwiat, Dimitrios Skarlatos and Charles Kamhoua. Their work appears in journals such as IEEE Micro and Rose-Hulman Scholar (Rose–Hulman Institute of Technology).
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.