Peng Qi

1.1k total citations · 1 hit paper
24 papers, 635 citations indexed

About

Peng Qi is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Peng Qi has authored 24 papers receiving a total of 635 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 6 papers in Information Systems and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Peng Qi's work include Sentiment Analysis and Opinion Mining (4 papers), Topic Modeling (4 papers) and Advanced Text Analysis Techniques (3 papers). Peng Qi is often cited by papers focused on Sentiment Analysis and Opinion Mining (4 papers), Topic Modeling (4 papers) and Advanced Text Analysis Techniques (3 papers). Peng Qi collaborates with scholars based in China, United States and Qatar. Peng Qi's co-authors include Yuhao Zhang, Christopher D. Manning, Yan Sun, Hong Luo, Tat‐Seng Chua, Junbin Xiao, Wei Ji, Juan Cao, Hongchao Chen and Xinhua Zhu and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Industrial Informatics and Neural Networks.

In The Last Decade

Peng Qi

20 papers receiving 613 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.

Graph Convolution over Pruned Dependency Trees Improves Relation Extraction

2018 510 citations Yuhao Zhang, Peng Qi et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Peng Qi China	7	557	80	64	63	45	24	635
Qinmin Hu Canada	13	635 1.1×	137 1.7×	65 1.0×	88 1.4×	33 0.7×	49	723
Ganggao Zhu Spain	5	311 0.6×	58 0.7×	44 0.7×	28 0.4×	35 0.8×	6	373
Xuanjing Huang China	11	542 1.0×	78 1.0×	35 0.5×	66 1.0×	31 0.7×	42	622
Johannes Deleu Belgium	9	517 0.9×	93 1.2×	89 1.4×	36 0.6×	15 0.3×	32	584
Minlong Peng China	9	484 0.9×	77 1.0×	20 0.3×	61 1.0×	16 0.4×	21	556
Ruidan He Singapore	13	814 1.5×	91 1.1×	23 0.4×	78 1.2×	39 0.9×	14	874
Anastasia Shimorina France	6	396 0.7×	50 0.6×	26 0.4×	67 1.1×	16 0.4×	11	478
Dan Gillick United States	12	666 1.2×	61 0.8×	27 0.4×	66 1.0×	19 0.4×	16	720
Khuyagbaatar Batsuren Italy	9	237 0.4×	47 0.6×	39 0.6×	59 0.9×	13 0.3×	12	351
Olga Uryupina Italy	14	943 1.7×	78 1.0×	73 1.1×	83 1.3×	42 0.9×	32	1.0k

Countries citing papers authored by Peng Qi

Since Specialization

Citations

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

Fields of papers citing papers by Peng Qi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peng Qi

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Tao, Dan, et al.. (2025). Scalable Large Model for Unlabeled Anomaly Detection With Trio-Attention U-Transformer and Manifold-Learning Siamese Discriminator. IEEE Transactions on Services Computing. 18(2). 1012–1025.

2.

Qi, Peng, Yu Chen, Wei Li, et al.. (2025). Coupled Drilling Optimization Based on Hybrid Physics-Machine Learning Models. Offshore Technology Conference.

3.

Tao, Dan, et al.. (2024). Anomaly Detection for MEC Enabled Hierarchical Industrial IoT With Transformer Enhanced Variational Auto Encoder. IEEE Transactions on Industrial Informatics. 21(1). 40–48. 2 indexed citations

4.

Gao, Ruipeng, Xuyu Wang, Hua Chai, et al.. (2024). Real-World Large-Scale Cellular Localization for Pickup Position Recommendation at Black-Hole. IEEE Transactions on Mobile Computing. 23(12). 15114–15131. 1 indexed citations

5.

Tao, Dan, et al.. (2024). Rethinking Discrepancy Analysis: Anomaly Detection via Meta-Learning Powered Dual-Source Representation Differentiation. IEEE Transactions on Automation Science and Engineering. 22. 8579–8592. 3 indexed citations

6.

Qi, Peng, et al.. (2024). Music-induced emotion flow modeling by ENMI Network. PLoS ONE. 19(10). e0297712–e0297712.

7.

Qi, Peng, et al.. (2024). KEMoS: A knowledge-enhanced multi-modal summarizing framework for Chinese online meetings. Neural Networks. 178. 106417–106417. 1 indexed citations

8.

Qi, Peng, et al.. (2023). FakeSV: A Multimodal Benchmark with Rich Social Context for Fake News Detection on Short Video Platforms. Proceedings of the AAAI Conference on Artificial Intelligence. 37(12). 14444–14452. 36 indexed citations

9.

Qi, Peng, Yan Sun, Hong Luo, & Mohsen Guizani. (2022). Scratch-Rec: a novel Scratch recommendation approach adapting user preference and programming skill for enhancing learning to program. Applied Intelligence. 52(8). 9423–9440. 3 indexed citations

10.

Jiang, Hao, et al.. (2021). A Short Survey on Forest Based Heterogeneous Treatment Effect Estimation Methods: Meta-learners and Specific Models. 2021 IEEE International Conference on Big Data (Big Data). 3006–3012. 3 indexed citations

11.

Qi, Peng, et al.. (2021). ScratchGAN: Network representation learning for scratch with preference‐based generative adversarial nets. International Journal of Intelligent Systems. 37(8). 4537–4560. 4 indexed citations

12.

Huang, Jing, et al.. (2021). Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification. 83–93. 19 indexed citations

13.

Qi, Peng, et al.. (2020). A Neural Network-based Sentiment Analysis Scheme for Tang Poetry. 1783–1788. 6 indexed citations

14.

Gao, Zijing, et al.. (2020). A Novel Music Emotion Recognition Model for Scratch-generated Music. 1794–1799. 8 indexed citations

15.

Zhao, Shuaifei, et al.. (2020). A Novel Image Classification Model Jointing Attention and ResNet for Scratch. 1498–1503. 2 indexed citations

16.

Qi, Peng, Yan Sun, Hong Luo, & Mohsen Guizani. (2020). Scratch-DKG: A Framework for Constructing Scratch Domain Knowledge Graph. IEEE Transactions on Emerging Topics in Computing. 10(1). 170–185. 7 indexed citations

17.

Xu, Can, Zhiyong Feng, Peng Qi, & Yan Sun. (2020). An Automatic Analysis Tool Based on Computational Thinking for BlockPy Programs. 2045–2050. 1 indexed citations

18.

Zhang, Yuhao, Peng Qi, & Christopher D. Manning. (2018). Graph Convolution over Pruned Dependency Trees Improves Relation Extraction. 2205–2215. 510 indexed citations breakdown →

19.

Zhu, Xinhua, Fei Li, Hongchao Chen, & Peng Qi. (2017). An efficient path computing model for measuring semantic similarity using edge and density. Knowledge and Information Systems. 55(1). 79–111. 15 indexed citations

20.

Qi, Peng. (2000). Qualitative Analysis for a Class of Second Order Nonlinear System. 1 indexed citations

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.

Explore authors with similar magnitude of impact