Zhichun Guo

845 citations
12 papers · 251 indexed · h-index 8
Topics
Machine Learning in Materials Science (4 papers)Computational Drug Discovery Methods (3 papers)Topic Modeling (3 papers)
Journals
Chemical ScienceWorld Wide WebProceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

In The Last Decade

Zhichun Guo

10 papers receiving 248 citations

Peers

Zhichun Guo
Comparison fields: 5 of 61
  • Materials Chemistry 99
  • Computational Theory and Mathematics 90
  • Artificial Intelligence 87
  • Molecular Biology 63
  • Information Systems 34
Replace Shufang Xie with:
Shufang Xie China
Yuquan Li China
Brian Belgodere United States
Dávid Lányi Switzerland
P. Balamurugan India
Inkit Padhi United States
Axel J. Soto Canada
Yisong Yue United States
Konstantinos Pliakos Belgium
Zhichun Guo relative to Shufang Xie China Shufang Xie's profile →
Citations per field
00.5×1.5×2.4×
Shufang Xie · 1×
Citations per year

Countries citing papers authored by Zhichun Guo

Since Specialization
Citations

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

Fields of papers citing papers by Zhichun Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhichun Guo

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 1
2 80
3 20
4 35
5 0
6 35
7 9
8 17
9 17
10 0
11 34
12 3

About Zhichun Guo

Zhichun Guo is a scholar working on Physical and Theoretical Chemistry, Computational Theory and Mathematics and Computer Science Applications, having authored 12 papers that have together received 251 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), Computational Drug Discovery Methods (3 papers) and Topic Modeling (3 papers). The work is most often cited by research in Computational Theory and Mathematics (90 citations), Artificial Intelligence (87 citations) and Materials Chemistry (99 citations). Zhichun Guo has collaborated with scholars based in United States, Sweden and Hong Kong. Frequent co-authors include Nitesh V. Chawla, Chuxu Zhang, Olaf Wiest, Per‐Ola Norrby, John E. Herr, Wenhao Yu, Meng Jiang, Thierry Kogej, Mengxia Yu and A. Zuranski. Their work appears in journals such as Chemical Science, World Wide Web and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

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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