James J. Sharp

1.1k total citations · 1 hit paper
56 papers, 548 citations indexed

About

James J. Sharp is a scholar working on Civil and Structural Engineering, Ecology and Artificial Intelligence. According to data from OpenAlex, James J. Sharp has authored 56 papers receiving a total of 548 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Civil and Structural Engineering, 9 papers in Ecology and 9 papers in Artificial Intelligence. Recurrent topics in James J. Sharp's work include Hydrology and Sediment Transport Processes (9 papers), Water Systems and Optimization (8 papers) and Adversarial Robustness in Machine Learning (8 papers). James J. Sharp is often cited by papers focused on Hydrology and Sediment Transport Processes (9 papers), Water Systems and Optimization (8 papers) and Adversarial Robustness in Machine Learning (8 papers). James J. Sharp collaborates with scholars based in Canada, United Kingdom and United States. James J. Sharp's co-authors include Youcheng Sun, Xiaowei Huang, Daniel Kroening, Wenjie Ruan, Min Wu, Xinping Yi, Matthew Q. Hill, Rob Ashmore, Trimbak M. Parchure and Emily E. Moore and has published in prestigious journals such as Fuel, Journal of the Franklin Institute and Advances in Water Resources.

In The Last Decade

James J. Sharp

45 papers receiving 523 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability

2020 259 citations Xiaowei Huang, Daniel Kroening et al. Computer Science Review profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
James J. Sharp Canada	9	310	94	70	56	41	56	548
Diego Alonso Spain	10	102 0.3×	51 0.5×	70 1.0×	7 0.1×	32 0.8×	34	339
Giulia DeSalvo United States	6	306 1.0×	5 0.1×	114 1.6×	19 0.3×	33 0.8×	14	598
Ruirui Huang China	11	141 0.5×	26 0.3×	112 1.6×	9 0.2×	32 0.8×	45	579
Liliana Perescu-Popescu Romania	6	106 0.3×	7 0.1×	57 0.8×	11 0.2×	45 1.1×	12	457
Chen Zeng China	10	125 0.4×	9 0.1×	53 0.8×	9 0.2×	23 0.6×	32	355
Sheng Jiang China	13	88 0.3×	6 0.1×	31 0.4×	94 1.7×	38 0.9×	27	558
Ziliang Feng China	13	59 0.2×	35 0.4×	165 2.4×	55 1.0×	10 0.2×	57	443
Wei Yuan China	14	82 0.3×	28 0.3×	277 4.0×	12 0.2×	22 0.5×	57	615
Sanjukta De India	5	136 0.4×	4 0.0×	58 0.8×	20 0.4×	27 0.7×	11	525

Countries citing papers authored by James J. Sharp

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of James J. Sharp

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

All Works

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20 of 20 papers shown

1.

Huang, Xiaowei, Daniel Kroening, Wenjie Ruan, et al.. (2020). A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability. Computer Science Review. 37. 100270–100270. 259 indexed citations breakdown →

2.

Sun, Youcheng, et al.. (2020). Reliability Validation of Learning Enabled Vehicle Tracking. Research Explorer (The University of Manchester). 9390–9396. 4 indexed citations

3.

Huang, Wei, Youcheng Sun, James J. Sharp, & Xiaowei Huang. (2019). Test Metrics for Recurrent Neural Networks.. arXiv (Cornell University). 2 indexed citations

4.

Huang, Xiaowei, Daniel Kroening, Wenjie Ruan, et al.. (2018). A Survey of Safety and Trustworthiness of Deep Neural Networks. arXiv (Cornell University). 5 indexed citations

5.

Sharp, James J., et al.. (1996). Numerical Model for Sea Outfall Hydraulics. Journal of Hydraulic Engineering. 122(2). 82–89. 5 indexed citations

6.

Sharp, James J., et al.. (1996). Characteristics of Radial Jets and Mixing under Buoyant Conditions. Journal of Hydraulic Engineering. 122(9). 495–502. 2 indexed citations

7.

Sharp, James J.. (1994). Field Tests on Small Marine Outfall. Journal of Environmental Engineering. 120(2). 471–477. 1 indexed citations

8.

Sharp, James J. & Muriel T. Davisson. (1994). The Jackson Laboratory Induced Mutant Resource.. The Mouseion at the JAXlibrary (Jackson Laboratory). 32. 7 indexed citations

9.

Sharp, James J. & Trimbak M. Parchure. (1993). Selective Withdrawal Using Circular, Partly Submerged Intake Structures. Journal of Hydraulic Engineering. 119(5). 615–627. 9 indexed citations

10.

Sharp, James J.. (1991). Marine outfalls for small coastal communities in Atlantic Canada. Canadian Journal of Civil Engineering. 18(3). 388–396. 5 indexed citations

11.

Sharp, James J.. (1990). Does Higher Education Promote Independent Learning? A Discussion; [and] In Response to James J. Sharp.. Higher Education. 20(3).

12.

Sharp, James J.. (1990). Does higher education promote independent learning? A discussion. Higher Education. 20(3). 335–336. 6 indexed citations

13.

Toft, Peter Andreas, R.S. Tobin, & James J. Sharp. (1989). Drinking water treatment : small system alternatives : proceedings of the Third National Conference on Drinking Water, St. John's, Newfoundland, Canada, June 12 to 14, 1988. Pergamon eBooks. 1 indexed citations

14.

Sharp, James J.. (1988). BASIC fluid mechanics. Butterworths eBooks. 5 indexed citations

15.

Allen, James H. & James J. Sharp. (1987). Environmental considerations for ocean outfalls and land-based treatment plants. Canadian Journal of Civil Engineering. 14(3). 363–371. 1 indexed citations

16.

Sharp, James J.. (1982). Treatment of fuel peat to enhance moisture removal. Fuel. 61(8). 741–744. 3 indexed citations

17.

Moore, Emily E. & James J. Sharp. (1979). Direct analytical solutions for approximate surge analysis. Advances in Water Resources. 2. 145–147. 1 indexed citations

18.

Sharp, James J., et al.. (1974). Arrested Wedge in Circular Tube. Journal of the Hydraulics Division. 100(7). 1085–1088. 3 indexed citations

19.

Sharp, James J.. (1972). Distorted Modeling of Density Currents. 39. 2339–2354.

20.

Sharp, James J.. (1971). Unsteady Spread of Buoyant Surface Discharge. Journal of the Hydraulics Division. 97(9). 1471–1492. 3 indexed citations

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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