Kensen Shi

2.4k citations
7 papers · 171 indexed · h-index 5
Topics
Software Engineering Research (2 papers)Robotics and Sensor-Based Localization (2 papers)Natural Language Processing Techniques (2 papers)
Journals
King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology)arXiv (Cornell University)International Conference on Machine Learning
Partner nations
United States

In The Last Decade

Kensen Shi

7 papers receiving 166 citations

Peers

Kensen Shi
Comparison fields: 5 of 26
  • Information Systems 104
  • Artificial Intelligence 67
  • Software 52
  • Computer Vision and Pattern Recognition 45
  • Signal Processing 38
Replace Ryan W. Gardner with:
Ryan W. Gardner United States
Noury Bouraqadi France
Michael Le United States
Richard Shin United States
Allan Tomlinson United Kingdom
Victor Heorhiadi United States
Yangruibo Ding United States
Nashwa Abdelbaki Egypt
Joshua Wright United States
Yong Ho Hwang South Korea
Kensen Shi relative to Ryan W. Gardner United States Ryan W. Gardner's profile →
Citations per field
00.5×3.8×
Ryan W. Gardner · 1×
Citations per year

Countries citing papers authored by Kensen Shi

Since Specialization
Citations

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

Fields of papers citing papers by Kensen Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kensen Shi

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

All Works

7 of 7 papers shown
#WorkIndexed citations
1 1
2 7
3
Incremental Sampling Without Replacement for Sequence Models
2
4
Pre-trained Contextual Embedding of Source Code
24
5 92
6 24
7 21

About Kensen Shi

Kensen Shi is a scholar working on Software, Signal Processing and Information Systems, having authored 7 papers that have together received 171 indexed citations. Recurring topics across this work include Software Engineering Research (2 papers), Robotics and Sensor-Based Localization (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Software (52 citations), Information Systems (104 citations) and Signal Processing (38 citations). Kensen Shi has collaborated with scholars based in United States. Frequent co-authors include Aditya Kanade, Gogul Balakrishnan, Petros Maniatis, Nancy M. Amato, Jory Denny, Michele Catasta, Pengcheng Yin, Yeming Wen, Henryk Michalewski and Kefan Xiao. Their work appears in journals such as King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology), arXiv (Cornell University) and International Conference on Machine Learning.

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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