Chudi Zhong

955 citations
3 papers · 474 indexed · 1 hit paper · h-index 3
Topics
Machine Learning and Data Classification (3 papers)Explainable Artificial Intelligence (XAI) (3 papers)Neural Networks and Applications (2 papers)
Journals
arXiv (Cornell University)Proceedings of the AAAI Conference on Artificial Intelligence
Partner nations
CanadaUnited States

In The Last Decade

Chudi Zhong

3 papers receiving 456 citations

Hit Papers

Interpretable machine learning: Fundamental principles an...20222026202320242022100200300400

Peers

Chudi Zhong
Comparison fields: 5 of 128
  • Artificial Intelligence 272
  • Computer Vision and Pattern Recognition 33
  • Health Informatics 31
  • Electrical and Electronic Engineering 29
  • Materials Chemistry 25
Replace Lesia Semenova with:
Lesia Semenova United States
Haiyang Huang China
Daniel Harborne United Kingdom
Tobias Leemann Germany
Katharina Beckh Germany
Rajkumar Ramamurthy Germany
Laura von Rueden Germany
Birgit Kirsch Germany
Angelos Chatzimparmpas Sweden
Chudi Zhong relative to Lesia Semenova United States Lesia Semenova's profile →
Citations per field
00.5×1.5×
Lesia Semenova · 1×
Citations per year

Countries citing papers authored by Chudi Zhong

Since Specialization
Citations

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

Fields of papers citing papers by Chudi Zhong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chudi Zhong

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

All Works

3 of 3 papers shown
#WorkIndexed citations
1 13
2
Interpretable machine learning: Fundamental principles and 10 grand challengesbreakdown →
440
3 21

About Chudi Zhong

Chudi Zhong is a scholar working on Artificial Intelligence, Infectious Diseases and Organic Chemistry, having authored 3 papers that have together received 474 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (3 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Health Informatics (31 citations), Artificial Intelligence (272 citations) and Safety Research (20 citations). Chudi Zhong has collaborated with scholars based in Canada and United States. Frequent co-authors include Cynthia Rudin, Zhi Chen, Haiyang Huang, Lesia Semenova, Chaofan Chen, Margo Seltzer, Diane Hu and Jimmy Lin. Their work appears in journals such as arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.

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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