Qimai Li

3.7k total citations · 1 hit paper
11 papers, 1.8k citations indexed

About

Qimai Li is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Qimai Li has authored 11 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Information Systems and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Qimai Li's work include Recommender Systems and Techniques (5 papers), Advanced Graph Neural Networks (5 papers) and Topic Modeling (2 papers). Qimai Li is often cited by papers focused on Recommender Systems and Techniques (5 papers), Advanced Graph Neural Networks (5 papers) and Topic Modeling (2 papers). Qimai Li collaborates with scholars based in Hong Kong, China and United States. Qimai Li's co-authors include Xiao-Ming Wu, Zhichao Han, Xiaotong Zhang, Han Liu, Lu Fan, Albert Y. S. Lam, Han Liu, Quanyu Dai, Han Liu and Dan Wang and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Knowledge and Data Engineering and Computer Communications.

In The Last Decade

Qimai Li

10 papers receiving 1.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning

2018 1.6k citations Qimai Li, Zhichao Han et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Qimai Li Hong Kong	7	1.3k	471	329	324	157	11	1.8k
Zhichao Han China	11	1.2k 1.0×	468 1.0×	301 0.9×	406 1.3×	220 1.4×	25	2.0k
Jiejun Xu United States	17	773 0.6×	432 0.9×	204 0.6×	243 0.8×	179 1.1×	48	1.6k
Xiao Luo China	23	784 0.6×	471 1.0×	203 0.6×	139 0.4×	165 1.1×	129	1.6k
Ziniu Hu United States	8	892 0.7×	217 0.5×	312 0.9×	232 0.7×	110 0.7×	12	1.2k
Akash Srivastava India	10	1.0k 0.8×	466 1.0×	258 0.8×	118 0.4×	147 0.9×	44	1.7k
Marion Neumann Germany	10	746 0.6×	293 0.6×	144 0.4×	258 0.8×	133 0.8×	18	1.1k
Yu Xie China	24	1.8k 1.4×	379 0.8×	383 1.2×	228 0.7×	117 0.7×	88	2.5k
Carl Yang United States	21	1.1k 0.9×	240 0.5×	435 1.3×	260 0.8×	175 1.1×	130	1.6k

Countries citing papers authored by Qimai Li

Since Specialization

Citations

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

Fields of papers citing papers by Qimai Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qimai Li

This figure shows the co-authorship network connecting the top 25 collaborators of Qimai Li. A scholar is included among the top collaborators of Qimai Li 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 Qimai Li. Qimai Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

1.

Liu, Han, Xiaotong Zhang, Qimai Li, et al.. (2023). Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors. 1195–1203. 1 indexed citations

2.

Zhang, Xiaotong, et al.. (2023). Adaptive Graph Convolution Methods for Attributed Graph Clustering. IEEE Transactions on Knowledge and Data Engineering. 35(12). 12384–12399. 6 indexed citations

3.

Dai, Quanyu, Xiao-Ming Wu, Lu Fan, et al.. (2022). Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks. Pattern Recognition. 128. 108628–108628. 31 indexed citations

4.

Fan, Lu, Qimai Li, Bo Liu, et al.. (2022). Modeling User Behavior with Graph Convolution for Personalized Product Search. Proceedings of the ACM Web Conference 2022. 203–212. 9 indexed citations

5.

Liu, Han, Xiaotong Zhang, Xianchao Zhang, Qimai Li, & Xiao-Ming Wu. (2021). RPC: Representative possible world based consistent clustering algorithm for uncertain data. Computer Communications. 176. 128–137. 5 indexed citations

6.

Chen, Jiaxin, et al.. (2020). A Closer Look at the Training Strategy for Modern Meta-Learning. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 33. 396–406. 4 indexed citations

7.

Fan, Lu, Qimai Li, Han Liu, et al.. (2020). Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification. 1050–1060. 41 indexed citations

8.

Li, Qimai, et al.. (2019). Label Efficient Semi-Supervised Learning via Graph Filtering. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 9574–9583. 116 indexed citations

9.

Liu, Han, Xiaotong Zhang, Lu Fan, et al.. (2019). Reconstructing Capsule Networks for Zero-shot Intent Classification. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 31 indexed citations

10.

Li, Qimai, et al.. (2018). Generalized Label Propagation Methods for Semi-Supervised Learning. arXiv (Cornell University).

11.

Li, Qimai, Zhichao Han, & Xiao-Ming Wu. (2018). Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 1551 indexed citations breakdown →

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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