Tingsong Jiang

731 citations
32 papers · 421 indexed · h-index 12
Topics
Adversarial Robustness in Machine Learning (22 papers)Anomaly Detection Techniques and Applications (7 papers)Advanced Neural Network Applications (6 papers)
Partner nations
ChinaUnited States

In The Last Decade

Tingsong Jiang

27 papers receiving 411 citations

Peers

Tingsong Jiang
Comparison fields: 5 of 59
  • Artificial Intelligence 361
  • Computer Vision and Pattern Recognition 105
  • Molecular Biology 50
  • Hardware and Architecture 50
  • Signal Processing 45
Replace Cheng Fu with:
Cheng Fu United States
Paishun Ting United States
Jiacheng Zhang China
Warren He United States
Donghua Wang China
Woosuk Kwon South Korea
Yunsheng Bai United States
Jamie Hayes United Kingdom
Xupeng Miao China
Firas Abuzaid United States
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Citations per field
00.5×11×
Cheng Fu · 1×
Citations per year

Countries citing papers authored by Tingsong Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Tingsong Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tingsong Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Tingsong Jiang. A scholar is included among the top collaborators of Tingsong Jiang 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 Tingsong Jiang. Tingsong Jiang 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
#WorkIndexed citations
1 0
2 0
3 0
4 8
5 0
6 2
7 3
8 8
9 7
10 1
11 4
12 12
13 14
14 13
15 16
16 1
17
Revisiting Distant Supervision for Relation Extraction
4
18 65
19
Towards Time-Aware Knowledge Graph Completion
47
20 15

About Tingsong Jiang

Tingsong Jiang is a scholar working on Artificial Intelligence, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 421 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (22 papers), Anomaly Detection Techniques and Applications (7 papers) and Advanced Neural Network Applications (6 papers). The work is most often cited by research in Artificial Intelligence (361 citations), Hardware and Architecture (50 citations) and Instrumentation (20 citations). Tingsong Jiang has collaborated with scholars based in China and United States. Frequent co-authors include Wen Yao, Zhifang Sui, Baobao Chang, Handing Wang, Donghua Wang, Xiaoqian Chen, Lei Sha, Sujian Li, Tao Ge and Jun Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

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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