Rongshan Yu

2.2k total citations
103 papers, 1.2k citations indexed

About

Rongshan Yu is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Rongshan Yu has authored 103 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Signal Processing, 38 papers in Computer Vision and Pattern Recognition and 23 papers in Molecular Biology. Recurrent topics in Rongshan Yu's work include Advanced Data Compression Techniques (26 papers), Speech and Audio Processing (17 papers) and Music and Audio Processing (13 papers). Rongshan Yu is often cited by papers focused on Advanced Data Compression Techniques (26 papers), Speech and Audio Processing (17 papers) and Music and Audio Processing (13 papers). Rongshan Yu collaborates with scholars based in Singapore, China and United States. Rongshan Yu's co-authors include Susanto Rahardja, Wenxian Yang, Wenxian Yang, Liansheng Wang, Chi Chung Ko, Xiaoliang Fan, Lequan Yu, Xiao Lin, Cheng Wang and Chenglu Wen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and Cancer Research.

In The Last Decade

Rongshan Yu

93 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rongshan Yu Singapore	18	290	250	241	223	206	103	1.2k
Minghui Wu China	20	345 1.2×	171 0.7×	181 0.8×	107 0.5×	101 0.5×	170	1.5k
Paul Salama United States	16	273 0.9×	468 1.9×	53 0.2×	219 1.0×	261 1.3×	115	1.1k
Shankar Vembu United States	15	366 1.3×	180 0.7×	409 1.7×	187 0.8×	343 1.7×	24	1.5k
G. Soda Italy	23	622 2.1×	538 2.2×	81 0.3×	127 0.6×	372 1.8×	110	1.9k
Mislav Grgić Croatia	22	441 1.5×	1.6k 6.6×	121 0.5×	593 2.7×	87 0.4×	114	2.7k
Dimitrios Makrakis Canada	25	357 1.2×	78 0.3×	1.0k 4.3×	89 0.4×	406 2.0×	205	2.3k
Cheng Zhong China	15	202 0.7×	224 0.9×	52 0.2×	105 0.5×	55 0.3×	45	665
Luis Rueda Canada	19	289 1.0×	106 0.4×	36 0.1×	90 0.4×	509 2.5×	122	1.1k
Hüseyin Şeker United Kingdom	14	339 1.2×	137 0.5×	67 0.3×	47 0.2×	219 1.1×	106	880

Countries citing papers authored by Rongshan Yu

Since Specialization

Citations

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

Fields of papers citing papers by Rongshan Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rongshan Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Rongshan Yu. A scholar is included among the top collaborators of Rongshan Yu 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 Rongshan Yu. Rongshan Yu 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:

20 of 20 papers shown

Chen, Ying, Guoan Wang, Yuanfeng Ji, et al.. (2025). SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding. 5134–5143.

Yang, Wenxian, et al.. (2025). Scoring information integration with statistical quality control enhanced cross-run analysis of data-independent acquisition proteomics data. Communications Chemistry. 8(1). 364–364. 1 indexed citations

Chen, Ying, et al.. (2024). PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation. Briefings in Bioinformatics. 25(6). 1 indexed citations

Wang, Zihui, Xiaoliang Fan, Yan Xu, et al.. (2024). ConTIG: Continuous representation learning on temporal interaction graphs. Neural Networks. 172. 106151–106151. 3 indexed citations

Lyu, Lingjuan, et al.. (2024). FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning. 3299–3310. 3 indexed citations

Chen, Ying, et al.. (2024). Tracing unknown tumor origins with a biological-pathway-based transformer model. Cell Reports Methods. 4(6). 100797–100797. 4 indexed citations

Tong, Mengsha, et al.. (2023). Prioritizing prognostic-associated subpopulations and individualized recurrence risk signatures from single-cell transcriptomes of colorectal cancer. Briefings in Bioinformatics. 24(3). 5 indexed citations

Lin, Yating, Haojun Li, Xu Xiao, et al.. (2022). DAISM-DNNXMBD: Highly accurate cell type proportion estimation with in silico data augmentation and deep neural networks. Patterns. 3(3). 100440–100440. 9 indexed citations

Yu, Lequan, et al.. (2022). MuRCL: Multi-Instance Reinforcement Contrastive Learning for Whole Slide Image Classification. IEEE Transactions on Medical Imaging. 42(5). 1337–1348. 30 indexed citations

10.

Yang, Wenxian, et al.. (2022). Application of individualized differential expression analysis in human cancer proteome. Briefings in Bioinformatics. 23(3). 5 indexed citations

11.

Cui, Chuanliang, Wenxian Yang, Zhihong Chi, et al.. (2021). Ratio of the interferon-γ signature to the immunosuppression signature predicts anti-PD-1 therapy response in melanoma. npj Genomic Medicine. 6(1). 7–7. 61 indexed citations

12.

Huang, Lihong, Bin Hong, Wenxian Yang, Liansheng Wang, & Rongshan Yu. (2021). Snipe: highly sensitive pathogen detection from metagenomic sequencing data. Briefings in Bioinformatics. 22(5). 4 indexed citations

13.

Gao, Mingxuan, Wenxian Yang, Chenxin Li, et al.. (2021). Deep representation features from DreamDIAXMBD improve the analysis of data-independent acquisition proteomics. Communications Biology. 4(1). 1190–1190. 17 indexed citations

14.

Yu, Rongshan & Wenxian Yang. (2020). ScaleQC: a scalable lossy to lossless solution for NGS data compression. Bioinformatics. 36(17). 4551–4559. 6 indexed citations

15.

Hu, Jing, Chuanliang Cui, Wenxian Yang, et al.. (2020). Using deep learning to predict anti-PD-1 response in melanoma and lung cancer patients from histopathology images. Translational Oncology. 14(1). 100921–100921. 48 indexed citations

16.

Gao, Mingxuan, Shun Wang, Xu Xiao, et al.. (2020). Comparison of high-throughput single-cell RNA sequencing data processing pipelines. Briefings in Bioinformatics. 22(3). 16 indexed citations

17.

Zheng, Chuanpan, et al.. (2019). Predicting ICU Mortality from Heterogeneous Clinical Events with Prior Medical Knowledge.. International Joint Conference on Artificial Intelligence. 55–59. 1 indexed citations

18.

Yu, Rongshan, et al.. (2012). Dynamic incentive strategy for voluntary demand response based on TDP scheme. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1–6. 8 indexed citations

19.

Jiang, Wenyu, et al.. (2012). Cloud-based audio fingerprinting service. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1–6. 1 indexed citations

20.

Huang, Haibin, et al.. (2010). An Introduction to AVS Lossless Audio Coding. Journal of the Audio Engineering Society. 3 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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