Seulbae Kim
Impact in
- Software top 2%
- Software Reliability and Analysis Research
- Software Testing and Debugging Techniques
- Signal Processing top 5%
- Advanced Malware Detection Techniques
Papers in
-
- Adversarial Robustness in Machine Learning 3
- Security and Verification in Computing 2
- Software 5
- Software Reliability and Analysis Research 3
- Software Testing and Debugging Techniques 3
- Co-authors
- Heejo Lee (4 shared papers)Hakjoo Oh (1 shared paper)Seunghoon Woo (1 shared paper)Taesoo Kim (4 shared papers)Wen Xu (2 shared papers)Sanidhya Kashyap (2 shared papers)Meng Xu (2 shared papers)Chung Hwan Kim (1 shared paper)
- Journals
- Computers & Security (1 paper)ACM Transactions on Storage (1 paper)IEEE Access (1 paper)arXiv (Cornell University) (1 paper)DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)
- Partner nations
- United StatesSouth KoreaUnited Arab Emirates
In The Last Decade
Seulbae Kim
8 papers receiving 356 citations
Seulbae Kim's Hit Papers
Peers
Comparison fields: 5 of 28
- Software 204
- Signal Processing 229
- Information Systems 250
- Hardware and Architecture 26
- Computer Networks and Communications 82
Countries citing papers authored by Seulbae Kim
This map shows the geographic impact of Seulbae Kim'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 Seulbae Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seulbae Kim more than expected).
Fields of papers citing papers by Seulbae Kim
This network shows the impact of papers produced by Seulbae Kim. 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 Seulbae Kim. The network helps show where Seulbae Kim may publish in the future.
Co-authors
The 17 scholars most cited alongside Seulbae Kim, 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 | VUDDY: A Scalable Approach for Vulnerable Code Clone Discovery Hit paper breakdown → | 2017 | 230 |
| 2 | 2019 | 50 | |
| 3 | 2022 | 30 | |
| 4 | 2018 | 28 | |
| 5 | 2022 | 13 | |
| 6 | 2021 | 10 | |
| 7 | 2020 | 5 | |
| 8 | SIGMATA: Storage Integrity Guaranteeing Mechanism against Tampering Attempts for Video Event Data Recorders | 2016 | 2 |
| 9 | 2025 | 0 |
About Seulbae Kim
Seulbae Kim is a scholar working on Artificial Intelligence, Software, Signal Processing, Computer Networks and Communications and Information Systems, having authored 9 papers that have together received 368 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (4 papers), Software Reliability and Analysis Research (3 papers), Software Testing and Debugging Techniques (3 papers), Adversarial Robustness in Machine Learning (3 papers), Advanced Data Storage Technologies (3 papers), Software Engineering Research (2 papers), Security and Verification in Computing (2 papers) and Cloud Data Security Solutions (1 paper). The work is most often cited by research in Software (204 citations), Signal Processing (229 citations), Information Systems (250 citations), Hardware and Architecture (26 citations) and Computer Networks and Communications (82 citations). Seulbae Kim has collaborated with scholars based in United States, South Korea and United Arab Emirates. Frequent co-authors include Heejo Lee, Hakjoo Oh, Seunghoon Woo, Taesoo Kim, Wen Xu, Sanidhya Kashyap, Meng Xu, Chung Hwan Kim, Yonghwi Kwon and Junghwan Rhee. Their work appears in journals such as Computers & Security, ACM Transactions on Storage, IEEE Access, arXiv (Cornell University) and DOAJ (DOAJ: Directory of Open Access Journals).
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.