James J. Sharp
Impact in
- Software top 5%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
- Health Informatics top 10%
Papers in ⓘ
- Software 4
- Software Testing and Debugging Techniques 4
- Co-authors
- Youcheng Sun (8 shared papers)Xiaowei Huang (8 shared papers)Daniel Kroening (5 shared papers)Wenjie Ruan (2 shared papers)Min Wu (2 shared papers)Xinping Yi (2 shared papers)Rob Ashmore (3 shared papers)Matthew Q. Hill (3 shared papers)
- Journals
- Journal of Hydraulic Engineering (6 papers)Canadian Journal of Civil Engineering (5 papers)Marine Structures (2 papers)Fuel (2 papers)Higher Education (2 papers)
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
James J. Sharp
45 papers receiving 523 citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Software 94
- Health Informatics 14
- Artificial Intelligence 310
- Signal Processing 38
- Computer Vision and Pattern Recognition 70
Countries citing papers authored by James J. Sharp
This map shows the geographic impact of James J. Sharp'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 James J. Sharp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James J. Sharp more than expected).
Fields of papers citing papers by James J. Sharp
This network shows the impact of papers produced by James J. Sharp. 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 James J. Sharp. The network helps show where James J. Sharp may publish in the future.
Co-authors
The 25 scholars most cited alongside James J. Sharp, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability Hit paper breakdown → | 2020 | 259 |
| 2 | 2019 | 57 | |
| 3 | 2019 | 40 | |
| 4 | 2019 | 18 | |
| 5 | 1996 | 13 | |
| 6 | 1991 | 13 | |
| 7 | 1969 | 13 | |
| 8 | 2000 | 10 | |
| 9 | 1993 | 9 | |
| 10 | 1969 | 8 | |
| 11 | The Jackson Laboratory Induced Mutant Resource. | 1994 | 7 |
| 12 | 1991 | 7 | |
| 13 | 1992 | 7 | |
| 14 | 1990 | 6 | |
| 15 | 1990 | 6 | |
| 16 | BASIC fluid mechanics | 1988 | 5 |
| 17 | A Survey of Safety and Trustworthiness of Deep Neural Networks | 2018 | 5 |
| 18 | 1996 | 5 | |
| 19 | 1991 | 5 | |
| 20 | 1983 | 5 |
About James J. Sharp
James J. Sharp is a scholar working on Architecture, Software, Civil and Structural Engineering, Oceanography and Ecology, having authored 56 papers that have together received 548 indexed citations. Recurring topics across this work include Hydrology and Sediment Transport Processes (9 papers), Hydraulic flow and structures (8 papers), Water Systems and Optimization (8 papers), Adversarial Robustness in Machine Learning (8 papers), Anomaly Detection Techniques and Applications (6 papers), Underwater Acoustics Research (5 papers), Software Testing and Debugging Techniques (4 papers) and Dam Engineering and Safety (4 papers). The work is most often cited by research in Software (94 citations), Health Informatics (14 citations), Artificial Intelligence (310 citations), Signal Processing (38 citations) and Computer Vision and Pattern Recognition (70 citations). James J. Sharp has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Youcheng Sun, Xiaowei Huang, Daniel Kroening, Wenjie Ruan, Min Wu, Xinping Yi, Rob Ashmore, Matthew Q. Hill, Trimbak M. Parchure and Emily E. Moore. Their work appears in journals such as Journal of Hydraulic Engineering, Canadian Journal of Civil Engineering, Marine Structures, Fuel and Higher Education.
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.