Lanshi Nie

48 total papers · 644 total citations
33 papers, 489 citations indexed

About

Lanshi Nie is a scholar working on Artificial Intelligence, Pollution and Geochemistry and Petrology. According to data from OpenAlex, Lanshi Nie has authored 33 papers receiving a total of 489 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 13 papers in Pollution and 13 papers in Geochemistry and Petrology. Recurrent topics in Lanshi Nie's work include Geochemistry and Geologic Mapping (22 papers), Heavy metals in environment (13 papers) and Geological and Geochemical Analysis (11 papers). Lanshi Nie is often cited by papers focused on Geochemistry and Geologic Mapping (22 papers), Heavy metals in environment (13 papers) and Geological and Geochemical Analysis (11 papers). Lanshi Nie collaborates with scholars based in China, South Africa and France. Lanshi Nie's co-authors include Bimin Zhang, Xueqiu Wang, Zhixuan Han, Hanliang Liu, Qinghua Chi, Shanfa Xu, Jian Zhou, Xiangyi Guo, Mi Tian and Qingqing Liu and has published in prestigious journals such as The Science of The Total Environment, CATENA and Applied Geochemistry.

In The Last Decade

Lanshi Nie

31 papers receiving 474 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Lanshi Nie	217	200	130	119	80	33	489
Qinghua Chi	193 0.9×	165 0.8×	155 1.2×	68 0.6×	66 0.8×	36	443
Hanliang Liu	199 0.9×	158 0.8×	115 0.9×	69 0.6×	76 0.9×	60	502
Shanfa Xu	290 1.3×	187 0.9×	120 0.9×	65 0.5×	83 1.0×	16	465
Charles Gowing	106 0.5×	149 0.7×	46 0.4×	72 0.6×	47 0.6×	22	423
John G. Arnason	96 0.4×	132 0.7×	48 0.4×	174 1.5×	67 0.8×	23	475
Liam A. Bullock	77 0.4×	72 0.4×	136 1.0×	42 0.4×	122 1.5×	36	445
Goran Tasev	115 0.5×	190 0.9×	61 0.5×	59 0.5×	151 1.9×	70	436
P. J. Aruscavage	142 0.7×	133 0.7×	271 2.1×	68 0.6×	147 1.8×	29	535
Harry Warren	97 0.4×	190 0.9×	45 0.3×	122 1.0×	19 0.2×	40	493
Zhizhong Cheng	333 1.5×	145 0.7×	69 0.5×	37 0.3×	156 1.9×	36	526

Countries citing papers authored by Lanshi Nie

Since Specialization

Citations

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

Fields of papers citing papers by Lanshi Nie

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lanshi Nie

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

All Works

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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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