Xi Lin

2.6k citations
39 papers · 1.3k · h-index 15

Impact in

    • Phytochemicals and Antioxidant Activities
    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Graph Neural Networks
    • Metaheuristic Optimization Algorithms Research

Papers in

Xi Lin

35 papers receiving 1.2k citations

Peers

Xi Lin
Comparison fields: 5 of 135
  • Biochemistry 217
  • Artificial Intelligence 538
  • Cellular and Molecular Neuroscience 137
  • Food Science 129
  • Management Science and Operations Research 72
Replace Hiroyuki Watanabe with:
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Dan Huang China
Miao Zhang China
Muhammad Shoaib Siddiqui Saudi Arabia
A. Das India
Masayuki Suzuki Japan
André Sales Barreto Brazil
Xiujuan Wang China
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Xi Lin relative to Hiroyuki Watanabe Japan Hiroyuki Watanabe's profile →
Citations per field
00.5×8.8×
Hiroyuki Watanabe · 1×
Citations per year

Countries citing papers authored by Xi Lin

Since Specialization
Citations

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

Fields of papers citing papers by Xi Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xi Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xi Lin Line = papers co-authored together Xi Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012257
2 2018201
3 2012192
4 202097
5 201975
6 199962
7 202057
8 200152
9 202248
10 200544
11 201837
12 202122
13 201617
14 202315
15 201715
16 201914
17 20218
18 19937
19 20226
20 20176

About Xi Lin

Xi Lin is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Sociology and Political Science, Molecular Biology and Cellular and Molecular Neuroscience, having authored 39 papers that have together received 1.3k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Topic Modeling (8 papers), Metaheuristic Optimization Algorithms Research (7 papers), Advanced Multi-Objective Optimization Algorithms (7 papers), Evolutionary Algorithms and Applications (3 papers), Multimodal Machine Learning Applications (3 papers), Genetic Neurodegenerative Diseases (3 papers) and Optimization and Packing Problems (2 papers). The work is most often cited by research in Biochemistry (217 citations), Artificial Intelligence (538 citations), Cellular and Molecular Neuroscience (137 citations), Food Science (129 citations) and Management Science and Operations Research (72 citations). Xi Lin has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Caiming Xiong, Richard Socher, Xiang‐Rong Xu, Qingfu Zhang, Huda Y. Zoghbi, Zhenhua Li, Tetsuo Ashizawa, Christopher J. Cummings, Hai‐Lin Liu and Hua‐Bin Li. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, International Journal of Bio-Inspired Computation, IEEE Transactions on Emerging Topics in Computational Intelligence, Neuron and Journal of Functional Foods.

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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