Taifeng Wang
- Artificial Intelligence top 0.5%
- Topic Modeling 12
- Natural Language Processing Techniques 10
- Advanced Text Analysis Techniques 4
- Stochastic Gradient Optimization Techniques 4
- Advanced Graph Neural Networks 4
- Health Information Management top 0.5%
- Environmental Engineering top 2%
- Signal Processing top 2%
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- Web Data Mining and Analysis 7
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- Complex Network Analysis Techniques 4
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- Multimodal Machine Learning Applications 4
- Journals
- Nature Methods (1 paper)IEEE Transactions on Cybernetics (1 paper)Signal Processing Image Communication (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Taifeng Wang
32 papers receiving 7.1k citations
Hit Papers
Peers
Comparison fields: 5 of 218
- Artificial Intelligence 2.3k
- Health Information Management 215
- Environmental Engineering 600
- Signal Processing 415
- Management Science and Operations Research 478
Countries citing papers authored by Taifeng Wang
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
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
The 25 scholars most cited alongside Taifeng Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Large-scale foundation model on single-cell transcriptomicsbreakdown → | 2024 | 150 |
| 2 | 2022 | 1 | |
| 3 | 2021 | 42 | |
| 4 | 2021 | 83 | |
| 5 | Light Gradient Boosting Machine [R package lightgbm version 3.2.0] | 2021 | 1 |
| 6 | 2021 | 0 | |
| 7 | 2020 | 6 | |
| 8 | 2020 | 70 | |
| 9 | 2020 | 30 | |
| 10 | 2018 | 68 | |
| 11 | 2017 | 14 | |
| 12 | Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning. | 2016 | 11 |
| 13 | Asynchronous accelerated stochastic gradient descent | 2016 | 8 |
| 14 | 2016 | 1 | |
| 15 | 2015 | 13 | |
| 16 | 2014 | 184 | |
| 17 | 2012 | 30 | |
| 18 | 2011 | 40 | |
| 19 | 2011 | 5 | |
| 20 | 2006 | 3 |
About Taifeng Wang
Taifeng Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Signal Processing, having authored 33 papers that have together received 7.4k indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (10 papers), Web Data Mining and Analysis (7 papers), Advanced Text Analysis Techniques (4 papers), Complex Network Analysis Techniques (4 papers), Stochastic Gradient Optimization Techniques (4 papers), Multimodal Machine Learning Applications (4 papers) and Advanced Graph Neural Networks (4 papers). The work is most often cited by research in Artificial Intelligence (2.3k citations), Health Information Management (215 citations), Environmental Engineering (600 citations), Signal Processing (415 citations) and Management Science and Operations Research (478 citations). Taifeng Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent 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. Their work appears in journals such as Nature Methods, IEEE Transactions on Cybernetics, Signal Processing Image Communication, Information Retrieval and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.