Ling-Xiao Cui

666 citations
14 papers · 448 indexed · 1 hit paper · h-index 8
Topics
Stock Market Forecasting Methods (5 papers)Black Holes and Theoretical Physics (5 papers)High-Energy Particle Collisions Research (4 papers)
Partner nations
China

In The Last Decade

Ling-Xiao Cui

14 papers receiving 438 citations

Hit Papers

Deep learning-based feature engineering for stock price m...20182026202020232018100200300

Peers

Ling-Xiao Cui
Comparison fields: 5 of 67
  • Management Science and Operations Research 279
  • Electrical and Electronic Engineering 134
  • Economics and Econometrics 117
  • Finance 105
  • Artificial Intelligence 64
Replace Eduardo Ruiz with:
Eduardo Ruiz United States
S. Alonso Monsalve Spain
Igor Halperin United States
Robert W. Keener United States
Suryoday Basak United States
Ashadun Nobi Bangladesh
Ian Buckley United States
Yilin Ma China
Carlo Mari Italy
Massimo Di Pierro United States
Ling-Xiao Cui relative to Eduardo Ruiz United States Eduardo Ruiz's profile →
Citations per field
00.5×10×13.4×
Eduardo Ruiz · 1×
Citations per year

Countries citing papers authored by Ling-Xiao Cui

Since Specialization
Citations

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

Fields of papers citing papers by Ling-Xiao Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling-Xiao Cui. 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 Ling-Xiao Cui. The network helps show where Ling-Xiao Cui may publish in the future.

Co-authorship network of co-authors of Ling-Xiao Cui

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 3
2 3
3
Deep learning-based feature engineering for stock price movement predictionbreakdown →
311
4 22
5 21
6 6
7 1
8 23
9 1
10 13
11 20
12 9
13 8
14 7

About Ling-Xiao Cui

Ling-Xiao Cui is a scholar working on Management Science and Operations Research, Finance and Nuclear and High Energy Physics, having authored 14 papers that have together received 448 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (5 papers), Black Holes and Theoretical Physics (5 papers) and High-Energy Particle Collisions Research (4 papers). The work is most often cited by research in Management Science and Operations Research (279 citations), Finance (105 citations) and Nuclear and High Energy Physics (59 citations). Ling-Xiao Cui has collaborated with scholars based in China. Frequent co-authors include Wen Long, Yue-Liang Wu, Zhen Fang, Yong Shi, Shingo Takeuchi, Fan Yang, Bin Wang, Hao Guo, Si Chen and Huiwen He. Their work appears in journals such as Green Chemistry, Journal of High Energy Physics and Physica A Statistical Mechanics and its Applications.

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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