Cong Chen

35 papers receiving 342 citations

Peers

Cong Chen
Comparison fields: 5 of 65
  • Statistics and Probability 174
  • Management Science and Operations Research 78
  • Cancer Research 68
  • Oncology 59
  • Statistics, Probability and Uncertainty 15
Replace Heng Zhou with:
Heng Zhou United States
NM Hylton United States
Emmanuel Zuber Switzerland
Sally Clive United Kingdom
Gautier Paux France
Thomas Gwise United States
Kyung Mann Kim United States
Zoran Antonijevic United States
Carl‐Fredrik Burman Sweden
Tie‐Hua Ng United States
Cong Chen relative to Heng Zhou United States Heng Zhou's profile →
Citations per field
00.5×1.5×
Heng Zhou · 1×
Citations per year

Countries citing papers authored by Cong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Cong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Cong Chen, 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 Cong Chen Line = papers co-authored together Cong Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201741
2 201438
3 201635
4 202031
5 201322
6 202017
7 202116
8 202015
9 201915
10 201711
11 201810
12 201710
13 20209
14 20219
15 20139
16 20027
17 20196
18 20215
19 20195
20 20215

About Cong Chen

Cong Chen is a scholar working on Statistics and Probability, Management Science and Operations Research, Modeling and Simulation, Cancer Research and Immunology, having authored 37 papers that have together received 353 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (27 papers), Optimal Experimental Design Methods (14 papers), Biosimilars and Bioanalytical Methods (7 papers), Cancer Genomics and Diagnostics (7 papers), Health Systems, Economic Evaluations, Quality of Life (6 papers), Mathematical Biology Tumor Growth (3 papers), Computational Drug Discovery Methods (2 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Statistics and Probability (174 citations), Management Science and Operations Research (78 citations), Cancer Research (68 citations), Oncology (59 citations) and Statistics, Probability and Uncertainty (15 citations). Cong Chen has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Eric H. Rubin, Linda Sun, Xiaoyun Li, Heng Zhou, Devan V. Mehrotra, Archie Tse, Robert A. Beckman, Cai Wu, Keaven M. Anderson and Haitao Yin. Their work appears in journals such as Contemporary Clinical Trials, Statistics in Biopharmaceutical Research, Statistics in Medicine, JCO Clinical Cancer Informatics and Pharmaceutical Statistics.

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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