Congrui Huang
- Artificial Intelligence top 2%
- Signal Processing top 2%
- Computer Networks and Communications top 5%
- Control and Systems Engineering top 10%
- Electrical and Electronic Engineering
- Topics
- Time Series Analysis and Forecasting (4 papers)Advanced Text Analysis Techniques (3 papers)Anomaly Detection Techniques and Applications (3 papers)
- Journals
- Empirical Methods in Natural Language ProcessingarXiv (Cornell University)Proceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Congrui Huang
7 papers receiving 862 citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 599
- Signal Processing 403
- Computer Networks and Communications 239
- Control and Systems Engineering 115
- Electrical and Electronic Engineering 72
Countries citing papers authored by Congrui Huang
This map shows the geographic impact of Congrui Huang'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 Congrui Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Congrui Huang more than expected).
Fields of papers citing papers by Congrui Huang
This network shows the impact of papers produced by Congrui Huang. 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 Congrui Huang. The network helps show where Congrui Huang may publish in the future.
Co-authorship network of co-authors of Congrui Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Congrui Huang. A scholar is included among the top collaborators of Congrui Huang 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 Congrui Huang. Congrui Huang 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 | 2 | |
| 3 | 4 | |
| 4 | TS2Vec: Towards Universal Representation of Time Seriesbreakdown → | 336 |
| 5 | 59 | |
| 6 | Multivariate Time-Series Anomaly Detection via Graph Attention Networkbreakdown → | 371 |
| 7 | 65 | |
| 8 | Timeline Generation through Evolutionary Trans-Temporal Summarization | 55 |
About Congrui Huang
Congrui Huang is a scholar working on Signal Processing, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 8 papers that have together received 892 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (4 papers), Advanced Text Analysis Techniques (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Signal Processing (403 citations), Artificial Intelligence (599 citations) and Computer Networks and Communications (239 citations). Congrui Huang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Juanyong Duan, Bixiong Xu, Yujing Wang, Yunhai Tong, Zhihan Yue, Tianmeng Yang, Jing Bai, Defu Cao, Jie Tong and Qi Zhang. Their work appears in journals such as Empirical Methods in Natural Language Processing, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.