Heyrim Cho

27 papers receiving 348 citations

Peers

Heyrim Cho
Comparison fields: 5 of 72
  • Modeling and Simulation 102
  • Statistics, Probability and Uncertainty 90
  • Computational Mathematics 5
  • Statistical and Nonlinear Physics 73
  • Oncology 106
Replace Erica M. Rutter with:
Erica M. Rutter United States
Alexander S. Bratus Russia
David J. Warne Australia
Alexander P. Browning Australia
Sabine Hug Germany
Wang Jin Australia
Christian Tönsing Germany
Qing Guo China
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Heyrim Cho relative to Erica M. Rutter United States Erica M. Rutter's profile →
Citations per field
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Erica M. Rutter · 1×
Citations per year

Countries citing papers authored by Heyrim Cho

Since Specialization
Citations

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

Fields of papers citing papers by Heyrim Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202074
2 201347
3 201143
4 201728
5 202321
6 201718
7 201318
8 201416
9 202311
10 201810
11 20209
12 20228
13 20188
14 20187
15 20207
16 20205
17 20155
18 20224
19 20164
20 20223

About Heyrim Cho

Heyrim Cho is a scholar working on Modeling and Simulation, Statistics, Probability and Uncertainty, Molecular Biology, Statistical and Nonlinear Physics and Oncology, having authored 30 papers that have together received 360 indexed citations. Recurring topics across this work include Mathematical Biology Tumor Growth (12 papers), Probabilistic and Robust Engineering Design (9 papers), Model Reduction and Neural Networks (8 papers), CAR-T cell therapy research (6 papers), Gene Regulatory Network Analysis (6 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Microtubule and mitosis dynamics (3 papers) and Single-cell and spatial transcriptomics (3 papers). The work is most often cited by research in Modeling and Simulation (102 citations), Statistics, Probability and Uncertainty (90 citations), Computational Mathematics (5 citations), Statistical and Nonlinear Physics (73 citations) and Oncology (106 citations). Heyrim Cho has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Daniele Venturi, George Em Karniadakis, Doron Levy, Russell C. Rockne, Themistoklis P. Sapsis, Christine E. Brown, Margarita Gutova, Vikram Adhikarla, Prativa Sahoo and Dongrui Wang. Their work appears in journals such as Mathematical Biosciences & Engineering, SIAM Journal on Scientific Computing, Journal of Theoretical Biology, Bulletin of Mathematical Biology and Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences.

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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