Sushan Li

818 total citations · 1 hit paper
6 papers, 540 citations indexed

About

Sushan Li is a scholar working on Statistics, Probability and Uncertainty, Civil and Structural Engineering and Pathology and Forensic Medicine. According to data from OpenAlex, Sushan Li has authored 6 papers receiving a total of 540 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Statistics, Probability and Uncertainty, 2 papers in Civil and Structural Engineering and 1 paper in Pathology and Forensic Medicine. Recurrent topics in Sushan Li's work include Probabilistic and Robust Engineering Design (5 papers), Fatigue and fracture mechanics (1 paper) and Aeroelasticity and Vibration Control (1 paper). Sushan Li is often cited by papers focused on Probabilistic and Robust Engineering Design (5 papers), Fatigue and fracture mechanics (1 paper) and Aeroelasticity and Vibration Control (1 paper). Sushan Li collaborates with scholars based in Germany, China and Italy. Sushan Li's co-authors include Qiongli Wu, Ksenia Aleksankina, Andrea Saltelli, Federico Ferretti, Niels Holst, William E. Becker, Pamela Fennell, Roland Platz, Jiasi Li and Lili Jiang and has published in prestigious journals such as Environmental Modelling & Software, Gland Surgery and arXiv (Cornell University).

In The Last Decade

Sushan Li

6 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.

Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices

2019 502 citations Andrea Saltelli, Ksenia Aleksankina et al. Environmental Modelling & Software profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sushan Li Germany	3	124	103	76	61	53	6	540
Ksenia Aleksankina United Kingdom	4	123 1.0×	120 1.2×	92 1.2×	58 1.0×	54 1.0×	4	582
Federico Ferretti Italy	6	165 1.3×	113 1.1×	78 1.0×	66 1.1×	56 1.1×	10	679
Qiongli Wu China	9	160 1.3×	129 1.3×	119 1.6×	74 1.2×	69 1.3×	19	727
Pamela Fennell United Kingdom	8	140 1.1×	188 1.8×	83 1.1×	58 1.0×	53 1.0×	25	692
Manchun Li China	16	86 0.7×	170 1.7×	151 2.0×	43 0.7×	19 0.4×	29	845
Paul Lemaître Canada	3	249 2.0×	87 0.8×	41 0.5×	105 1.7×	17 0.3×	4	655
Takuya Iwanaga Australia	12	64 0.5×	150 1.5×	189 2.5×	66 1.1×	175 3.3×	24	764
Ricardo Bolado Netherlands	3	113 0.9×	52 0.5×	47 0.6×	60 1.0×	36 0.7×	5	362
Liguo Zhang China	18	129 1.0×	90 0.9×	207 2.7×	33 0.5×	49 0.9×	116	1.1k
Tohid Erfani United Kingdom	13	56 0.5×	51 0.5×	50 0.7×	86 1.4×	178 3.4×	39	565

Countries citing papers authored by Sushan Li

Since Specialization

Citations

This map shows the geographic impact of Sushan Li'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 Sushan Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sushan Li more than expected).

Fields of papers citing papers by Sushan Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sushan Li. 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 Sushan Li. The network helps show where Sushan Li may publish in the future.

Co-authorship network of co-authors of Sushan Li

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

All Works

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6 of 6 papers shown

1.

Jiang, Lili, Jiasi Li, Jie Sun, et al.. (2021). A huge malignant phyllodes tumor of the breast with osteoclast-like giant cells: a case report. Gland Surgery. 10(4). 1508–1514. 6 indexed citations

2.

Saltelli, Andrea, Ksenia Aleksankina, William E. Becker, et al.. (2019). Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices. Environmental Modelling & Software. 114. 29–39. 502 indexed citations breakdown →

3.

Saltelli, Andrea, Ksenia Aleksankina, William E. Becker, et al.. (2017). Why So Many Published Sensitivity Analyses Are False. A Systematic Review of Sensitivity Analysis Practices. arXiv (Cornell University). 28 indexed citations

4.

Li, Sushan, et al.. (2017). Numerical uncertainty analysis of active and passive structures in the structural design phase. Procedia Engineering. 199. 1240–1245. 1 indexed citations

5.

Li, Sushan, et al.. (2017). APPROACH TO PROVE THE EFFICIENCY OF THE MONTE CARLO METHOD COMBINED WITH THE ELEMENTARY EFFECT METHOD TO QUANTIFY UNCERTAINTY OF A BEAM STRUCTURE WITH PIEZO-ELASTIC SUPPORTS. TUbilio (Technical University of Darmstadt). 441–455. 2 indexed citations

6.

Li, Sushan & Roland Platz. (2017). Observations by Evaluating the Uncertainty of Stress Distribution in Truss Structures Based on Probabilistic and Possibilistic Methods. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 2(3). 1 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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