Haicheng Tao

638 total citations
27 papers, 428 citations indexed

About

Haicheng Tao is a scholar working on Artificial Intelligence, Computer Networks and Communications and Statistical and Nonlinear Physics. According to data from OpenAlex, Haicheng Tao has authored 27 papers receiving a total of 428 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 8 papers in Computer Networks and Communications and 8 papers in Statistical and Nonlinear Physics. Recurrent topics in Haicheng Tao's work include Complex Network Analysis Techniques (8 papers), Network Security and Intrusion Detection (7 papers) and Anomaly Detection Techniques and Applications (6 papers). Haicheng Tao is often cited by papers focused on Complex Network Analysis Techniques (8 papers), Network Security and Intrusion Detection (7 papers) and Anomaly Detection Techniques and Applications (6 papers). Haicheng Tao collaborates with scholars based in China, United States and Australia. Haicheng Tao's co-authors include Jie Cao, Zhan Bu, Xingquan Zhu, Youquan Wang, Hui‐Jia Li, Weichao Liang, Guixiang Zhu, Lei Chen, Jia Wu and Jianshan Sun and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Industrial Informatics and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Haicheng Tao

24 papers receiving 414 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Haicheng Tao China	11	182	111	105	98	60	27	428
Yong Feng China	13	177 1.0×	199 1.8×	76 0.7×	102 1.0×	75 1.3×	70	548
Qi Cao China	12	357 2.0×	112 1.0×	195 1.9×	117 1.2×	79 1.3×	46	582
Taotao Cai Australia	10	288 1.6×	89 0.8×	196 1.9×	122 1.2×	112 1.9×	33	585
Chenyi Zhuang Japan	9	295 1.6×	138 1.2×	120 1.1×	98 1.0×	24 0.4×	29	469
Shanqing Yu China	12	252 1.4×	36 0.3×	129 1.2×	56 0.6×	73 1.2×	57	434
Anupam Biswas India	13	322 1.8×	60 0.5×	165 1.6×	48 0.5×	52 0.9×	53	537
Sungsu Lim South Korea	13	188 1.0×	68 0.6×	188 1.8×	74 0.8×	119 2.0×	49	455
Fabio Persia Italy	12	200 1.1×	186 1.7×	54 0.5×	222 2.3×	156 2.6×	63	546
Huaizhen Kou China	8	193 1.1×	66 0.6×	39 0.4×	152 1.6×	118 2.0×	20	393
Qi Liao United States	12	222 1.2×	140 1.3×	86 0.8×	113 1.2×	159 2.6×	56	546

Countries citing papers authored by Haicheng Tao

Since Specialization

Citations

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

Fields of papers citing papers by Haicheng Tao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haicheng Tao

This figure shows the co-authorship network connecting the top 25 collaborators of Haicheng Tao. A scholar is included among the top collaborators of Haicheng Tao 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 Haicheng Tao. Haicheng Tao 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

Vuković, Darko, et al.. (2025). Fraud detection in multi-relation graph: Contrastive Learning on Feature and Structural Levels. Neurocomputing. 637. 130063–130063. 1 indexed citations

Tao, Haicheng, et al.. (2023). HAN-CAD: hierarchical attention network for context anomaly detection in multivariate time series. World Wide Web. 26(5). 2785–2800. 6 indexed citations

Tao, Haicheng, et al.. (2023). Black-box attacks on dynamic graphs via adversarial topology perturbations. Neural Networks. 171. 308–319. 9 indexed citations

Tao, Haicheng, et al.. (2023). Reconstruction-based anomaly detection for multivariate time series using contrastive generative adversarial networks. Information Processing & Management. 61(1). 103569–103569. 37 indexed citations

Chen, Lei, et al.. (2022). Trip Reinforcement Recommendation with Graph-based Representation Learning. ACM Transactions on Knowledge Discovery from Data. 17(4). 1–20. 24 indexed citations

Wang, Youquan, Zhiwen Dai, Jie Cao, et al.. (2022). Intra- and inter-association attention network-enhanced policy learning for social group recommendation. World Wide Web. 26(1). 71–94. 9 indexed citations

Cao, Jie, et al.. (2022). Sensor-based Human Activity Recognition Using Graph LSTM and Multi-task Classification Model. ACM Transactions on Multimedia Computing Communications and Applications. 18(3s). 1–19. 13 indexed citations

Zhang, Zhenyu, et al.. (2022). Time Series Anomaly Detection for Smart Grids via Multiple Self-Supervised Tasks Learning. 392–397. 3 indexed citations

Wang, Youquan, et al.. (2022). Inter- and Intra-Graph Attention Aggregation Learning for Multi-relational GNN Spam Detection. Procedia Computer Science. 214. 1522–1530. 1 indexed citations

10.

Chen, Lei, Jie Cao, Huanhuan Chen, et al.. (2021). Attentive multi-task learning for group itinerary recommendation. Knowledge and Information Systems. 63(7). 1687–1716. 22 indexed citations

11.

Wang, Youquan, Jie Cao, & Haicheng Tao. (2021). Graph convolutional network with multi-similarity attribute matrices fusion for node classification. Neural Computing and Applications. 35(18). 13135–13145. 10 indexed citations

12.

Cao, Jie, Yuyao Wang, Zhan Bu, et al.. (2021). Compactness Preserving Community Computation Via a Network Generative Process. IEEE Transactions on Emerging Topics in Computational Intelligence. 6(5). 1044–1056. 14 indexed citations

13.

Tao, Haicheng, et al.. (2020). A survey and taxonomy of adversarial neural networks for text‐to‐image synthesis. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 10(4). 76 indexed citations

14.

Cao, Jie, Youquan Wang, Jing He, et al.. (2020). Predicting Grain Losses and Waste Rate Along the Entire Chain: A Multitask Multigated Recurrent Unit Autoencoder Based Method. IEEE Transactions on Industrial Informatics. 17(6). 4390–4400. 19 indexed citations

15.

Tao, Haicheng, Zhe Li, Zhiang Wu, & Jie Cao. (2019). Link communities detection: an embedding method on the line hypergraph. Neurocomputing. 367. 46–54. 6 indexed citations

16.

Bu, Zhan, et al.. (2017). GLEAM: a graph clustering framework based on potential game optimization for large-scale social networks. Knowledge and Information Systems. 55(3). 741–770. 58 indexed citations

17.

Zhu, Xingquan, et al.. (2017). Fraud Prevention in Online Digital Advertising. SpringerBriefs in computer science. 22 indexed citations

18.

Cao, Jie, et al.. (2016). Weighted modularity optimization for crisp and fuzzy community detection in large-scale networks. Physica A Statistical Mechanics and its Applications. 462. 386–395. 59 indexed citations

19.

Tao, Haicheng, Zhiang Wu, Jin Shi, Jie Cao, & Xiaofeng Yu. (2014). Overlapping Community Extraction: A Link Hypergraph Partitioning Based Method. 123–130. 3 indexed citations

20.

Wu, Zhiang, Jie Cao, Haicheng Tao, & Yi Zhuang. (2013). A novel noise filter based on interesting pattern mining for bag-of-features images. Expert Systems with Applications. 40(18). 7555–7561. 4 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.

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