Ryan Cohn

1.1k total citations · 1 hit paper
6 papers, 734 citations indexed

About

Ryan Cohn is a scholar working on Materials Chemistry, Computer Vision and Pattern Recognition and Mechanical Engineering. According to data from OpenAlex, Ryan Cohn has authored 6 papers receiving a total of 734 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Materials Chemistry, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Mechanical Engineering. Recurrent topics in Ryan Cohn's work include X-ray Diffraction in Crystallography (2 papers), Machine Learning in Materials Science (2 papers) and Aluminum Alloys Composites Properties (1 paper). Ryan Cohn is often cited by papers focused on X-ray Diffraction in Crystallography (2 papers), Machine Learning in Materials Science (2 papers) and Aluminum Alloys Composites Properties (1 paper). Ryan Cohn collaborates with scholars based in United States and Germany. Ryan Cohn's co-authors include Elizabeth A. Holm, Francesca Tavazza, Anubhav Jain, Shyue Ping Ong, Alok Choudhary, Kamal Choudhary, Simon J. L. Billinge, Brian DeCost, Ankit Agrawal and Chi Chen and has published in prestigious journals such as Scientific Reports, Annual Review of Materials Research and JOM.

In The Last Decade

Ryan Cohn

5 papers receiving 713 citations

Hit Papers

Recent advances and applications of deep learning methods... 2022 2026 2023 2024 2022 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Recent advances and applications of deep learning methods in materials science
    2022 652 citations Kamal Choudhary, Brian DeCost et al. npj Computational Materials profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ryan Cohn United States 3 390 127 105 94 85 6 734
Dipendra Jha United States 9 645 1.7× 171 1.3× 104 1.0× 83 0.9× 64 0.8× 12 888
Guifang Shao China 19 403 1.0× 124 1.0× 135 1.3× 116 1.2× 79 0.9× 88 963
Qianxiao Li Singapore 15 448 1.1× 94 0.7× 177 1.7× 176 1.9× 185 2.2× 56 1.2k
Ruoqian Liu United States 9 525 1.3× 198 1.6× 111 1.1× 55 0.6× 54 0.6× 18 819
Qing Xia China 20 440 1.1× 143 1.1× 74 0.7× 54 0.6× 30 0.4× 62 956
Rongzhi Dong United States 16 418 1.1× 221 1.7× 126 1.2× 40 0.4× 84 1.0× 23 840
Kai Jiang China 16 197 0.5× 110 0.9× 39 0.4× 67 0.7× 73 0.9× 47 777
Dahui Liu China 13 271 0.7× 64 0.5× 119 1.1× 102 1.1× 35 0.4× 32 558

Countries citing papers authored by Ryan Cohn

Since Specialization
Citations

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

Fields of papers citing papers by Ryan Cohn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryan Cohn

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

All Works

6 of 6 papers shown
1.
Cohn, Ryan & Elizabeth A. Holm. (2024). Graph convolutional network for predicting abnormal grain growth in Monte Carlo simulations of microstructural evolution. Scientific Reports. 14(1). 30259–30259.
2.
Krill, Carl E., et al.. (2023). Extreme Abnormal Grain Growth: Connecting Mechanisms to Microstructural Outcomes. Annual Review of Materials Research. 53(1). 319–345. 17 indexed citations
3.
Choudhary, Kamal, Brian DeCost, Chi Chen, et al.. (2022). Recent advances and applications of deep learning methods in materials science. npj Computational Materials. 8(1). 652 indexed citations breakdown →
4.
5.
Cohn, Ryan & Elizabeth A. Holm. (2021). Unsupervised Machine Learning Via Transfer Learning and k-Means Clustering to Classify Materials Image Data. Integrating materials and manufacturing innovation. 10(2). 231–244. 62 indexed citations
6.
Cohn, Ryan, et al.. (2018). Calorimetric Study with Uncertainty Analysis to Investigate the Precipitation Kinetics in a Nanostructured Al Composite. Advanced Engineering Materials. 20(4). 2 indexed citations

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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