Jiarong Ye

421 total citations
10 papers, 207 citations indexed

About

Jiarong Ye is a scholar working on Biophysics, Infectious Diseases and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jiarong Ye has authored 10 papers receiving a total of 207 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Biophysics, 2 papers in Infectious Diseases and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jiarong Ye's work include Spectroscopy Techniques in Biomedical and Chemical Research (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Digital Imaging for Blood Diseases (2 papers). Jiarong Ye is often cited by papers focused on Spectroscopy Techniques in Biomedical and Chemical Research (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Digital Imaging for Blood Diseases (2 papers). Jiarong Ye collaborates with scholars based in China, United States and Macao. Jiarong Ye's co-authors include Yuan Xue, Xiaolei Huang, Sameer Antani, Zhiyun Xue, Richard J. Zaino, L. Rodney Long, Keith C. Cheng, Mauricio Terrones, Kunyan Zhang and Shengxi Huang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, ACS Nano and Scientific Reports.

In The Last Decade

Jiarong Ye

9 papers receiving 205 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jiarong Ye China	6	69	66	53	46	46	10	207
Bingfeng Luo China	10	51 0.7×	27 0.4×	45 0.8×	13 0.3×	3 0.1×	25	206
Lyudmila A. Bratchenko Russia	11	26 0.4×	249 3.8×	85 1.6×	15 0.3×	39 0.8×	40	331
Debora Smith United States	9	63 0.9×	102 1.5×	19 0.4×	5 0.1×	23 0.5×	16	319
Peng Zheng China	6	7 0.1×	104 1.6×	77 1.5×	14 0.3×	15 0.3×	17	196
Aman Rana United States	6	75 1.1×	38 0.6×	25 0.5×	35 0.8×	34 0.7×	16	185
Yulia А. Khristoforova Russia	10	27 0.4×	276 4.2×	101 1.9×	13 0.3×	70 1.5×	48	388
Sergey V. Kozlov Russia	10	27 0.4×	270 4.1×	107 2.0×	14 0.3×	94 2.0×	49	392
K. Kalyan Kumar India	9	18 0.3×	283 4.3×	42 0.8×	13 0.3×	47 1.0×	15	342
Oliver Old United Kingdom	8	11 0.2×	124 1.9×	29 0.5×	7 0.2×	19 0.4×	20	227
Eben Olson United States	6	36 0.5×	55 0.8×	31 0.6×	32 0.7×	20 0.4×	9	193

Countries citing papers authored by Jiarong Ye

Since Specialization

Citations

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

Fields of papers citing papers by Jiarong Ye

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiarong Ye

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Zhang, Ning, et al.. (2025). Unveiling lactylation modification: A new hope for cancer treatment. Biomedicine & Pharmacotherapy. 184. 117934–117934. 6 indexed citations

2.

Ye, Jiarong, Shivam Kalra, & Mohammad Saleh Miri. (2024). Cluster-based histopathology phenotype representation learning by self-supervised multi-class-token hierarchical ViT. Scientific Reports. 14(1). 3202–3202. 2 indexed citations

3.

Jin, Peng, Yin‐Ting Yeh, Jiarong Ye, et al.. (2023). Strain-Level Identification and Analysis of Avian Coronavirus Using Raman Spectroscopy and Interpretable Machine Learning. 1–5.

4.

Ye, Jiarong, et al.. (2023). Hotspots, trends, and advice: a 10-year visualization-based analysis of painting therapy from a scientometric perspective. Frontiers in Psychology. 14. 1148391–1148391. 2 indexed citations

5.

Ye, Jiarong, Yin‐Ting Yeh, Yuan Xue, et al.. (2022). Accurate virus identification with interpretable Raman signatures by machine learning. Proceedings of the National Academy of Sciences. 119(23). 44 indexed citations

6.

Ye, Jiarong, Kunyan Zhang, Ding Li, et al.. (2022). Rapid Biomarker Screening of Alzheimer’s Disease by Interpretable Machine Learning and Graphene-Assisted Raman Spectroscopy. ACS Nano. 16(4). 6426–6436. 51 indexed citations

7.

Ye, Jiarong, et al.. (2022). A Rare Cause of Black Pleural Effusion. The American Journal of Medicine. 136(2). e17–e19. 1 indexed citations

8.

Xue, Yuan, Jiarong Ye, L. Rodney Long, et al.. (2020). Selective synthetic augmentation with HistoGAN for improved histopathology image classification. Medical Image Analysis. 67. 101816–101816. 88 indexed citations

9.

Ye, Jiarong, et al.. (2020). Avoiding hospital-related infections during the COVID-19 epidemic. Critical Care. 24(1). 206–206. 8 indexed citations

10.

Ye, Jiarong, et al.. (2018). Efficacy and safety of Shenfu injection for patients with return of spontaneous circulation after sudden cardiac arrest. Medicine. 97(38). e12500–e12500. 5 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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