Kai Wei

848 citations
37 papers · 500 · h-index 11

Impact in

    • Machine Learning and Algorithms
    • Topic Modeling
    • Speech Recognition and Synthesis
    • Natural Language Processing Techniques
    • Machine Learning and Data Classification

Papers in

    • Bioinformatics and Genomic Networks 12
    • Gene expression and cancer classification 5
    • Topic Modeling 5
    • Natural Language Processing Techniques 4
    • Speech and dialogue systems 3
    • Machine Learning and Algorithms 3

Kai Wei

32 papers receiving 476 citations

Peers

Kai Wei
Comparison fields: 5 of 116
  • Artificial Intelligence 243
  • Signal Processing 54
  • Agronomy and Crop Science 39
  • Computational Theory and Mathematics 54
  • Computer Vision and Pattern Recognition 64
Replace Yin Ye with:
Yin Ye China
Niina Haiminen United States
Jinyu Yang China
Bahar Ali Pakistan
Yongbin Zhou China
Isobel Claire Gormley Ireland
Sanfeng Chen China
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Kai Wei relative to Yin Ye China Yin Ye's profile →
Citations per field
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Citations per year

Countries citing papers authored by Kai Wei

Since Specialization
Citations

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

Fields of papers citing papers by Kai Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kai Wei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kai Wei Line = papers co-authored together Kai Wei links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Submodularity in Data Subset Selection and Active Learning
2015104
2 2018102
3 201446
4 201333
5
Using Document Summarization Techniques for Speech Data Subset Selection
201329
6 201328
7 202125
8 201422
9 202114
10 202212
11 202112
12
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications
201510
13
Algorithms for optimizing the ratio of submodular functions
20169
14 20228
15 20217
16 20235
17 20234
18 20223
19 20253
20 20213

About Kai Wei

Kai Wei is a scholar working on Molecular Biology, Artificial Intelligence, Cognitive Neuroscience, Signal Processing and Physiology, having authored 37 papers that have together received 500 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (12 papers), Functional Brain Connectivity Studies (7 papers), Topic Modeling (5 papers), Gene expression and cancer classification (5 papers), Natural Language Processing Techniques (4 papers), Alzheimer's disease research and treatments (3 papers), Speech and dialogue systems (3 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (243 citations), Signal Processing (54 citations), Agronomy and Crop Science (39 citations), Computational Theory and Mathematics (54 citations) and Computer Vision and Pattern Recognition (64 citations). Kai Wei has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Jeff Bilmes, Rishabh Iyer, Katrin Kirchhoff, Yuzong Liu, Shuaiqun Wang, Wei Kong, Na Liu, He Huang, Lin Zhu and Yulin Xu. Their work appears in journals such as Journal of Molecular Neuroscience, Optical Engineering, Frontiers in Aging Neuroscience, Antimicrobial Agents and Chemotherapy and IEEE Access.

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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