Dejiao Zhang
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Computational Mechanics
- Information Systems
- Signal Processing
- Co-authors
- Henghui ZhuRamesh NallapatiBing XiangLaura BalzanoKathleen McKeownAndrew O. ArnoldShang-Wen LiNan Feng
- Topics
- Topic Modeling (11 papers)Natural Language Processing Techniques (10 papers)Sparse and Compressive Sensing Techniques (5 papers)
- Journals
- Image and Vision ComputingEmpirical Methods in Natural Language ProcessingDeep Blue (University of Michigan)
- Partner nations
- United StatesChinaPortugal
In The Last Decade
Dejiao Zhang
19 papers receiving 410 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 313
- Computer Vision and Pattern Recognition 134
- Computational Mechanics 48
- Information Systems 34
- Signal Processing 18
Countries citing papers authored by Dejiao Zhang
This map shows the geographic impact of Dejiao Zhang'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 Dejiao Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dejiao Zhang more than expected).
Fields of papers citing papers by Dejiao Zhang
This network shows the impact of papers produced by Dejiao Zhang. 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 Dejiao Zhang. The network helps show where Dejiao Zhang may publish in the future.
Co-authorship network of co-authors of Dejiao Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Dejiao Zhang. A scholar is included among the top collaborators of Dejiao Zhang 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 Dejiao Zhang. Dejiao Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 3 | |
| 4 | 13 | |
| 5 | 5 | |
| 6 | 118 | |
| 7 | 68 | |
| 8 | 46 | |
| 9 | 31 | |
| 10 | 9 | |
| 11 | 5 | |
| 12 | Unsupervised Domain Adaptation for Cross-lingual Text Labeling. | 4 |
| 13 | Extracting Compact Knowledge From Massive Data | 0 |
| 14 | LEARNING TO SHARE: SIMULTANEOUS PARAMETER TYING AND SPARSIFICATION IN DEEP LEARNING | 18 |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 2 | |
| 18 | Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation | 20 |
| 19 | 42 | |
| 20 | 13 |
About Dejiao Zhang
Dejiao Zhang is a scholar working on Artificial Intelligence, Signal Processing and Computational Mechanics, having authored 21 papers that have together received 425 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers) and Sparse and Compressive Sensing Techniques (5 papers). The work is most often cited by research in Computational Mathematics (8 citations), Artificial Intelligence (313 citations) and Computer Vision and Pattern Recognition (134 citations). Dejiao Zhang has collaborated with scholars based in United States, China and Portugal. Frequent co-authors include Henghui Zhu, Ramesh Nallapati, Bing Xiang, Laura Balzano, Kathleen McKeown, Andrew O. Arnold, Shang-Wen Li, Nan Feng, Xiaokai Wei and Cícero Nogueira dos Santos. Their work appears in journals such as Image and Vision Computing, Empirical Methods in Natural Language Processing and Deep Blue (University of Michigan).
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.