Taifeng Wang

11.7k total citations · 2 hit papers
33 papers, 7.4k citations indexed

About

Taifeng Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Taifeng Wang has authored 33 papers receiving a total of 7.4k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 9 papers in Information Systems. Recurrent topics in Taifeng Wang's work include Topic Modeling (12 papers), Natural Language Processing Techniques (10 papers) and Web Data Mining and Analysis (7 papers). Taifeng Wang is often cited by papers focused on Topic Modeling (12 papers), Natural Language Processing Techniques (10 papers) and Web Data Mining and Analysis (7 papers). Taifeng Wang collaborates with scholars based in China, United States and United Kingdom. Taifeng Wang's co-authors include Tie‐Yan Liu, Qi Meng, Wei Chen, Qiwei Ye, Thomas Finley, Weidong Ma, Guolin Ke, Yuyu Zhang, Jianshan He and Wei Chu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Nature Methods and IEEE Transactions on Cybernetics.

In The Last Decade

Taifeng Wang

32 papers receiving 7.1k citations

Hit Papers

align trajectories

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.

LightGBM: A Highly Efficient Gradient Boosting Decision Tree

2017 6.5k citations Guolin Ke, Qi Meng et al. profile →
Large-scale foundation model on single-cell transcriptomics

2024 150 citations Minsheng Hao, Jing Gong et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Taifeng Wang China	15	2.3k	716	666	647	600	33	7.4k
Guolin Ke China	13	2.5k 1.1×	805 1.1×	492 0.7×	613 0.9×	624 1.0×	22	8.0k
Zigang Lu China	6	2.1k 0.9×	687 1.0×	435 0.7×	522 0.8×	660 1.1×	17	8.8k
Qi Meng China	9	1.9k 0.8×	731 1.0×	419 0.6×	533 0.8×	611 1.0×	21	6.7k
Weidong Ma China	13	1.9k 0.8×	721 1.0×	440 0.7×	529 0.8×	633 1.1×	50	6.9k
Qiwei Ye China	5	1.8k 0.8×	718 1.0×	414 0.6×	529 0.8×	603 1.0×	8	6.7k
Thomas Finley United States	11	2.8k 1.2×	717 1.0×	715 1.1×	598 0.9×	609 1.0×	17	8.0k
Davide Chicco Canada	22	2.5k 1.1×	652 0.9×	510 0.8×	1.3k 2.0×	560 0.9×	70	9.5k
Giuseppe Jurman Italy	28	2.3k 1.0×	626 0.9×	546 0.8×	1.7k 2.7×	577 1.0×	97	9.9k
Darrell Whitley United States	31	3.2k 1.4×	886 1.2×	813 1.2×	356 0.6×	589 1.0×	143	7.6k
José M. Benítez Spain	36	2.6k 1.1×	543 0.8×	806 1.2×	523 0.8×	277 0.5×	119	5.8k

Countries citing papers authored by Taifeng Wang

Since Specialization

Citations

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

Fields of papers citing papers by Taifeng Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taifeng Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Taifeng Wang. A scholar is included among the top collaborators of Taifeng Wang 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 Taifeng Wang. Taifeng Wang 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

1.

Hao, Minsheng, Jing Gong, Xin Zeng, et al.. (2024). Large-scale foundation model on single-cell transcriptomics. Nature Methods. 21(8). 1481–1491. 150 indexed citations breakdown →

2.

Xu, Jun, et al.. (2022). Extracting Trigger-sharing Events via an Event Matrix. 1189–1201. 1 indexed citations

3.

Yang, Hang, Dianbo Sui, Yubo Chen, et al.. (2021). Document-level Event Extraction via Parallel Prediction Networks. 6298–6308. 42 indexed citations

4.

Chao, Linlin, Jianshan He, Taifeng Wang, & Wei Chu. (2021). PairRE: Knowledge Graph Embeddings via Paired Relation Vectors. 4360–4369. 83 indexed citations

5.

Ke, Guolin, James Lamb, Thomas Finley, et al.. (2021). Light Gradient Boosting Machine [R package lightgbm version 3.2.0]. 1 indexed citations

6.

Chen, Pei, Kang Liu, Yubo Chen, Taifeng Wang, & Jun Zhao. (2021). Probing into the Root: A Dataset for Reason Extraction of Structural Events from Financial Documents. 2042–2048.

7.

Chen, Pei, Hang Yang, Kang Liu, et al.. (2020). Reconstructing Event Regions for Event Extraction via Graph Attention Networks. 811–820. 6 indexed citations

8.

Cheng, Xingyi, Weidi Xu, Kunlong Chen, et al.. (2020). SpellGCN: Incorporating Phonological and Visual Similarities into Language Models for Chinese Spelling Check. 871–881. 70 indexed citations

9.

Chen, Kunlong, Weidi Xu, Xingyi Cheng, et al.. (2020). Question Directed Graph Attention Network for Numerical Reasoning over Text. 6759–6768. 30 indexed citations

10.

Yao, Quanming, James T. Kwok, Taifeng Wang, & Tie‐Yan Liu. (2018). Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers. IEEE Transactions on Pattern Analysis and Machine Intelligence. 41(11). 2628–2643. 68 indexed citations

11.

Liu, Tie‐Yan, Wei Chen, & Taifeng Wang. (2017). Distributed Machine Learning. 913–915. 14 indexed citations

12.

Zheng, Shuxin, Qi Meng, Taifeng Wang, et al.. (2016). Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning.. arXiv (Cornell University). 11 indexed citations

13.

Meng, Qi, et al.. (2016). Asynchronous accelerated stochastic gradient descent. International Joint Conference on Artificial Intelligence. 1853–1859. 8 indexed citations

14.

Yu, Nenghai, et al.. (2016). Ada-Sal Network: emulate the Human Visual System. Signal Processing Image Communication. 47. 519–528. 1 indexed citations

15.

Wei, Wei, Bin Gao, Tie‐Yan Liu, et al.. (2015). A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information. IEEE Transactions on Cybernetics. 46(4). 930–944. 13 indexed citations

16.

Zhang, Yuyu, Hanjun Dai, Chang Xu, et al.. (2014). Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 28(1). 184 indexed citations

17.

Xiong, Chenyan, Taifeng Wang, Wenkui Ding, Yi-Dong Shen, & Tie‐Yan Liu. (2012). Relational click prediction for sponsored search. 493–502. 30 indexed citations

18.

Gao, Bin, Tie‐Yan Liu, Wei Wei, Taifeng Wang, & Hang Li. (2011). Semi-supervised ranking on very large graphs with rich metadata. 96–104. 40 indexed citations

19.

Gao, Bin, Tie‐Yan Liu, Yuting Liu, et al.. (2011). Page importance computation based on Markov processes. Information Retrieval. 14(5). 488–514. 5 indexed citations

20.

Wang, Taifeng, Nenghai Yu, Zhiwei Li, & Mingjing Li. (2006). nReader. 1385–1390. 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.

Explore authors with similar magnitude of impact