Shaohua Sun
- Artificial Intelligence top 1%
- Management Science and Operations Research top 2%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 10%
- Co-authors
- Kevin MurphyEvgeniy GabrilovichXin Luna DongGeremy HeitzNi LaoWei ZhangRobert WestRahul Gupta
- Topics
- Topic Modeling (8 papers)Multimodal Machine Learning Applications (4 papers)Image Retrieval and Classification Techniques (3 papers)
- Cited by
- Artificial IntelligenceManagement Science and Operations ResearchComputer Science Applications
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Shaohua Sun
31 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 1.3k
- Management Science and Operations Research 375
- Information Systems 328
- Computer Vision and Pattern Recognition 289
- Signal Processing 92
Countries citing papers authored by Shaohua Sun
This map shows the geographic impact of Shaohua Sun'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 Shaohua Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaohua Sun more than expected).
Fields of papers citing papers by Shaohua Sun
This network shows the impact of papers produced by Shaohua Sun. 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 Shaohua Sun. The network helps show where Shaohua Sun may publish in the future.
Co-authorship network of co-authors of Shaohua Sun
This figure shows the co-authorship network connecting the top 25 collaborators of Shaohua Sun. A scholar is included among the top collaborators of Shaohua Sun 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 Shaohua Sun. Shaohua Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | Generalizable Imitation Learning from Observation via Inferring Goal Proximity | 2 |
| 8 | Program Guided Agent | 4 |
| 9 | 36 | |
| 10 | 19 | |
| 11 | Composing Complex Skills by Learning Transition Policies | 15 |
| 12 | Neural Program Synthesis from Diverse Demonstration Videos | 16 |
| 13 | Model-Agnostic Meta-Learning for Multimodal Task Distributions | 1 |
| 14 | 1 | |
| 15 | Allocation of Advertisement Extensions & Formats | 1 |
| 16 | 79 | |
| 17 | 1 | |
| 18 | 10 | |
| 19 | 53 | |
| 20 | 16 |
About Shaohua Sun
Shaohua Sun is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 35 papers that have together received 1.7k indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Multimodal Machine Learning Applications (4 papers) and Image Retrieval and Classification Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Management Science and Operations Research (375 citations) and Computer Science Applications (83 citations). Shaohua Sun has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Kevin Murphy, Evgeniy Gabrilovich, Xin Luna Dong, Geremy Heitz, Ni Lao, Wei Zhang, Robert West, Rahul Gupta, Dekang Lin and Yu-Chiang Frank Wang. Their work appears in journals such as Medical Physics, Remote Sensing and Proceedings of the VLDB Endowment.
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.