Haoming Jiang
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Mechanical Engineering
- Information Systems top 10%
- Mechanics of Materials
- Topics
- Topic Modeling (14 papers)Natural Language Processing Techniques (9 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- Journal of Machine Learning ResearchNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated EquipmentArabian Journal for Science and Engineering
- Partner nations
- United StatesChinaGermany
In The Last Decade
Haoming Jiang
31 papers receiving 620 citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 399
- Computer Vision and Pattern Recognition 112
- Mechanical Engineering 85
- Information Systems 83
- Mechanics of Materials 57
Countries citing papers authored by Haoming Jiang
This map shows the geographic impact of Haoming 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 Haoming Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haoming Jiang more than expected).
Fields of papers citing papers by Haoming Jiang
This network shows the impact of papers produced by Haoming 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 Haoming Jiang. The network helps show where Haoming Jiang may publish in the future.
Co-authorship network of co-authors of Haoming Jiang
This figure shows the co-authorship network connecting the top 25 collaborators of Haoming Jiang. A scholar is included among the top collaborators of Haoming 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 Haoming Jiang. Haoming Jiang 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 | 5 | |
| 3 | Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyondbreakdown → | 237 |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 14 | |
| 9 | 2 | |
| 10 | 24 | |
| 11 | 42 | |
| 12 | 12 | |
| 13 | Learning to Defense by Learning to Attack | 4 |
| 14 | 28 | |
| 15 | 28 | |
| 16 | Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds | 11 |
| 17 | Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks | 2 |
| 18 | On Computation and Generalization of Generative Adversarial Networks under Spectrum Control | 6 |
| 19 | Learning to Defense by Learning to Attack. | 4 |
| 20 | 3 |
About Haoming Jiang
Haoming Jiang is a scholar working on Health Informatics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 34 papers that have together received 646 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (9 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Health Informatics (31 citations), Artificial Intelligence (399 citations) and Computer Vision and Pattern Recognition (112 citations). Haoming Jiang has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Bing Yin, Jingfeng Yang, Shaochen Zhong, Hongye Jin, Qizhang Feng, Xiaotian Han, Ruixiang Tang, Xia Hu, Tuo Zhao and Chao Zhang. Their work appears in journals such as Journal of Machine Learning Research, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and Arabian Journal for Science and Engineering.
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.