Chengxi Ye

3.2k total citations · 1 hit paper
20 papers, 1.5k citations indexed

About

Chengxi Ye is a scholar working on Electrical and Electronic Engineering, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chengxi Ye has authored 20 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Electrical and Electronic Engineering, 7 papers in Molecular Biology and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chengxi Ye's work include Genomics and Phylogenetic Studies (6 papers), Advancements in Battery Materials (5 papers) and Advanced Battery Materials and Technologies (4 papers). Chengxi Ye is often cited by papers focused on Genomics and Phylogenetic Studies (6 papers), Advancements in Battery Materials (5 papers) and Advanced Battery Materials and Technologies (4 papers). Chengxi Ye collaborates with scholars based in China, United States and United Kingdom. Chengxi Ye's co-authors include Douglas W. Yu, Zhaoli Ding, Xiaoyang Wang, Chunyan Yang, Yinqiu Ji, Brent C. Emerson, Charles H. Cannon, Zhanshan Ma, Mihai Pop and Zhanshan Sam and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and Journal of The Electrochemical Society.

In The Last Decade

Chengxi Ye

20 papers receiving 1.4k citations

Hit Papers

Biodiversity soup: metabarcoding of arthropods for rapid ... 2012 2026 2016 2021 2012 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chengxi Ye China 14 714 629 210 202 199 20 1.5k
Col R. Ford United Kingdom 11 200 0.3× 212 0.3× 150 0.7× 78 0.4× 259 1.3× 15 895
Cong Wei China 18 234 0.3× 106 0.2× 251 1.2× 84 0.4× 234 1.2× 178 1.2k
Xing‐Xing Shen China 30 1.8k 2.5× 359 0.6× 960 4.6× 36 0.2× 659 3.3× 81 3.2k
Sheng‐Quan Xu China 15 799 1.1× 180 0.3× 155 0.7× 20 0.1× 172 0.9× 73 1.2k
Guoqing Lu United States 29 1.3k 1.8× 680 1.1× 277 1.3× 22 0.1× 1.1k 5.5× 96 3.2k
Seunghwan Lee South Korea 22 181 0.3× 253 0.4× 478 2.3× 82 0.4× 260 1.3× 189 1.8k
Matthew D. Clark United Kingdom 21 868 1.2× 338 0.5× 631 3.0× 11 0.1× 292 1.5× 45 1.9k
Lam Si Tung Ho United States 9 186 0.3× 261 0.4× 116 0.6× 28 0.1× 263 1.3× 24 1.1k
Daniel J. Aneshansley United States 27 315 0.4× 351 0.6× 877 4.2× 68 0.3× 589 3.0× 81 2.6k
Sean M. O’Rourke United States 13 1.4k 1.9× 157 0.2× 355 1.7× 18 0.1× 308 1.5× 33 1.8k

Countries citing papers authored by Chengxi Ye

Since Specialization
Citations

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

Fields of papers citing papers by Chengxi Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chengxi Ye

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

All Works

20 of 20 papers shown
2.
Zhang, Xian, Jingzheng Weng, Chengxi Ye, et al.. (2022). Strategies for Controlling or Releasing the Influence Due to the Volume Expansion of Silicon inside Si−C Composite Anode for High-Performance Lithium-Ion Batteries. Materials. 15(12). 4264–4264. 34 indexed citations
3.
Ye, Chengxi, et al.. (2022). Exploiting Invariance in Training Deep Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 36(8). 8849–8856. 1 indexed citations
4.
Ye, Chengxi, et al.. (2021). Research progress in electrochemical properties of lithium batteries with PAA binders. SHILAP Revista de lepidopterología. 1 indexed citations
5.
Ye, Chengxi, et al.. (2021). Review—Long-Term Cyclability of High-Temperature Stable Polyimide in LIBs. Journal of The Electrochemical Society. 168(10). 100519–100519. 13 indexed citations
6.
Shu, Yijin, Zhaojie Li, Yang Yang, et al.. (2021). Isolated Cobalt Atoms on N-Doped Carbon as Nanozymes for Hydrogen Peroxide and Dopamine Detection. ACS Applied Nano Materials. 4(8). 7954–7962. 67 indexed citations
7.
Ye, Chengxi, et al.. (2021). Influence of Binder on Impedance of Lithium Batteries: A Mini-review. Journal of Electrical Engineering and Technology. 17(2). 1281–1291. 23 indexed citations
8.
Ye, Chengxi, Anton Mitrokhin, Cornelia Fermüller, James A. Yorke, & Yiannis Aloimonos. (2020). Unsupervised Learning of Dense Optical Flow, Depth and Egomotion with Event-Based Sensors. 5831–5838. 34 indexed citations
9.
Mitrokhin, Anton, Chengxi Ye, Cornelia Fermüller, Yiannis Aloimonos, & Tobi Delbrück. (2019). EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras. 6105–6112. 64 indexed citations
10.
Ye, Chengxi, Anton Mitrokhin, Chethan M. Parameshwara, et al.. (2018). Unsupervised Learning of Dense Optical Flow and Depth from Sparse Event Data.. arXiv (Cornell University). 18 indexed citations
11.
Ma, Zhanshan, Lianwei Li, Chengxi Ye, Min‐Sheng Peng, & Ya‐Ping Zhang. (2018). Hybrid assembly of ultra-long Nanopore reads augmented with 10x-Genomics contigs: Demonstrated with a human genome. Genomics. 111(6). 1896–1901. 20 indexed citations
12.
Ye, Chengxi & Zhanshan Ma. (2016). Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads. PeerJ. 4. e2016–e2016. 23 indexed citations
13.
Ye, Chengxi, Chen Zhao, Yezhou Yang, Cornelia Fermüller, & Yiannis Aloimonos. (2016). LightNet. 1156–1159. 13 indexed citations
14.
Ye, Chengxi, C. Hill, Shigang Wu, Jue Ruan, & Zhanshan Ma. (2016). DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Scientific Reports. 6(1). 31900–31900. 206 indexed citations
16.
Ye, Chengxi, Chiaowen Joyce Hsiao, & Héctor Corrada Bravo. (2014). BlindCall: ultra-fast base-calling of high-throughput sequencing data by blind deconvolution. Bioinformatics. 30(9). 1214–1219. 7 indexed citations
17.
Wang, Bo, Chengxi Ye, Charles H. Cannon, & Jin Chen. (2012). Dissecting the decision making process of scatter‐hoarding rodents. Oikos. 122(7). 1027–1034. 69 indexed citations
18.
Yu, Douglas W., Yinqiu Ji, Brent C. Emerson, et al.. (2012). Biodiversity soup: metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Methods in Ecology and Evolution. 3(4). 613–623. 529 indexed citations breakdown →
19.
Ye, Chengxi, Zhanshan Sam, Charles H. Cannon, Mihai Pop, & Douglas W. Yu. (2012). Exploiting sparseness in de novo genome assembly. BMC Bioinformatics. 13(S6). S1–S1. 296 indexed citations
20.
Ye, Chengxi, et al.. (2009). Viewpoint independent vehicle speed estimation from uncalibrated traffic surveillance cameras. 1. 4920–4925. 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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