Geng Chen

504 total citations
13 papers, 291 citations indexed

About

Geng Chen is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Geng Chen has authored 13 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computational Theory and Mathematics, 4 papers in Molecular Biology and 3 papers in Materials Chemistry. Recurrent topics in Geng Chen's work include Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (3 papers) and Protein Structure and Dynamics (2 papers). Geng Chen is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (3 papers) and Protein Structure and Dynamics (2 papers). Geng Chen collaborates with scholars based in China, United States and Mexico. Geng Chen's co-authors include Ivan Stojmenović, Fabián García Nocetti, J. Solano, Mingyue Zheng, Xutong Li, Dingyan Wang, Hualiang Jiang, Xiaomin Luo, Jie Yu and Xiaoqin Tan and has published in prestigious journals such as Biosensors and Bioelectronics, Journal of Chemical Information and Modeling and Computers in Biology and Medicine.

In The Last Decade

Geng Chen

9 papers receiving 269 citations

Peers

Geng Chen
Comparison fields: 5 of 59
  • Computer Networks and Communications 170
  • Computational Theory and Mathematics 72
  • Electrical and Electronic Engineering 63
  • Molecular Biology 48
  • Artificial Intelligence 24
Replace Charles Siegel with:
Charles Siegel United States
Rainer G. Spallek Germany
Sandrine Vial France
Koki Hamada Japan
Adele A. Rescigno Italy
Marcin Bieńkowski Poland
Davide Gadioli Italy
Swen Boehm United States
Joe Ryan Australia
Charles Siegel United States View profile →
Citations per field, relative to Geng Chen
Geng Chen · 1×
Citations per year, relative to Geng Chen
Geng Chen · 1×

Countries citing papers authored by Geng Chen

Since Specialization
Citations

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

Fields of papers citing papers by Geng Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Geng Chen

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

All Works

13 of 13 papers shown
# Work Indexed citations
1 0
2 0
3 0
4 0
5 3
6 19
7 21
8 29
9 22
10 7
11
Doppler compensation on underwater acoustic wideband signals
2
12 15
13 173

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026