Hao Peng

10.3k total citations · 6 hit papers
177 papers, 5.1k citations indexed

About

Hao Peng is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Hao Peng has authored 177 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Artificial Intelligence, 30 papers in Information Systems and 20 papers in Computer Networks and Communications. Recurrent topics in Hao Peng's work include Topic Modeling (48 papers), Advanced Graph Neural Networks (47 papers) and Complex Network Analysis Techniques (18 papers). Hao Peng is often cited by papers focused on Topic Modeling (48 papers), Advanced Graph Neural Networks (47 papers) and Complex Network Analysis Techniques (18 papers). Hao Peng collaborates with scholars based in China, United States and Australia. Hao Peng's co-authors include Philip S. Yu, Jianxin Li, Lifang He, Lihong Wang, Senzhang Wang, Renyu Yang, Bowen Du, Yunchuan Chen, Zhi Jin and Lili Mou and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Computers in Human Behavior.

In The Last Decade

Hao Peng

167 papers receiving 4.9k citations

Hit Papers

5 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.

Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths

2015 415 citations Hao Peng et al. profile →
Using probabilistic generative models for ranking risks of Android apps

2012 260 citations Hao Peng et al. profile →
Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting

2020 243 citations Hao Peng, Bowen Du et al. Information Sciences profile →
Deep Irregular Convolutional Residual LSTM for Urban Traffic Passenger Flows Prediction

2019 225 citations Bowen Du, Hao Peng et al. profile →
A Survey on Text Classification: From Traditional to Deep Learning

2022 218 citations Qian Li, Hao Peng et al. ACM Transactions on Intelligent Systems and Technology profile →
Dynamic graph convolutional network for long-term traffic flow prediction with reinforcement learning

2021 164 citations Hao Peng, Bowen Du et al. Information Sciences profile →

Peers

Countries citing papers authored by Hao Peng

Since Specialization

Citations

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

Fields of papers citing papers by Hao Peng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hao Peng

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

#	Work	Indexed citations
1	Stimulation intensities influence the effects of spinal cord stimulation in disorders of consciousness: an fNIRS study 2025 ·Neurophotonics ·(unknown), (unknown), Jiao Li, Hao Peng, (unknown), (unknown), Qin Zhang, (unknown), (unknown)	0
2	Leakage Detection in Water Distribution Systems Based on Logarithmic Spectrogram CNN for Continuous Monitoring 2024 ·Journal of Water Resources Planning and Management ·Hao Peng, (unknown), (unknown), Liqiang Qi, Haitao Wang	9
3	TADGCN: A Time-Aware Dynamic Graph Convolution Network for long-term traffic flow prediction 2024 ·Expert Systems with Applications ·(unknown), (unknown), (unknown), Chunyang Liu, Hao Peng, Wenjie Li, (unknown), Peng Hu, (unknown), Biao Jie	5
4	SEBot: Structural Entropy Guided Multi-View Contrastive learning for Social Bot Detection 2024 ·(unknown), (unknown), (unknown), Hao Peng, Renyu Yang, (unknown), (unknown)	8
5	Motif-Aware Riemannian Graph Neural Network with Generative-Contrastive Learning 2024 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Li Sun, (unknown), (unknown), Feiyang Wang, Hao Peng, Philip S. Yu	4
6	Event Extraction by Associating Event Types and Argument Roles 2023 ·IEEE Transactions on Big Data ·Qian Li, Shu Guo, Jia Wu, Jianxin Li, Jiawei Sheng, Hao Peng, Lihong Wang	8
7	Unbiased and Efficient Self-Supervised Incremental Contrastive Learning 2023 ·Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, (unknown), Qingyun Sun, Philip S. Yu	4
8	How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers 2022 ·(unknown), Hao Peng, (unknown), Jungo Kasai, (unknown), Noah A. Smith, Roy Schwartz	9
9	Adaptive Pre-Training and Collaborative Fine-Tuning: A Win-Win Strategy to Improve Review Analysis Tasks 2022 ·IEEE/ACM Transactions on Audio Speech and Language Processing ·(unknown), Jianxin Li, Chenghua Lin, (unknown), Hao Peng, Lihong Wang, Philip S. Yu	2
10	Multi-View Tensor Graph Neural Networks Through Reinforced Aggregation 2022 ·IEEE Transactions on Knowledge and Data Engineering ·Xusheng Zhao, Qiong Dai, Jia Wu, Hao Peng, Mingsheng Liu, Xu Bai, Jianlong Tan, Senzhang Wang, Philip S. Yu	30
11	Fact-Driven Abstractive Summarization by Utilizing Multi-Granular Multi-Relational Knowledge 2022 ·IEEE/ACM Transactions on Audio Speech and Language Processing ·(unknown), Jianxin Li, Hao Peng, Shizhu He, Lihong Wang, Philip S. Yu, Zheng Wang	8
12	Federated Multi-view Learning for Private Medical Data Integration and Analysis 2022 ·ACM Transactions on Intelligent Systems and Technology ·(unknown), (unknown), Hao Peng, Lichao Sun, Alex Leow, Yong Chen, Lifang He	27
13	What happens next? Combining enhanced multilevel script learning and dual fusion strategies for script event prediction 2022 ·International Journal of Intelligent Systems ·Pengpeng Zhou, Bin Wu, Caiyong Wang, Hao Peng, (unknown), (unknown)	3
14	Privacy-Preserving Federated Depression Detection From Multisource Mobile Health Data 2021 ·IEEE Transactions on Industrial Informatics ·(unknown), Hao Peng, Md Zakirul Alam Bhuiyan, (unknown), Lianzhong Liu, Lichao Sun, Lifang He	5
15	Lime: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks 2021 ·IEEE Transactions on Computers ·Hao Peng, Renyu Yang, Zheng Wang, Jianxin Li, Lifang He, Philip S. Yu, Albert Y. Zomaya, Rajiv Ranjan	55
16	More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction 2020 ·Xu Han, Tianyu Gao, Yankai Lin, Hao Peng, (unknown), Chaojun Xiao, Zhiyuan Liu, (unknown), Jie Zhou, Maosong Sun	33
17	Learning from Context or Names? An Empirical Study on Neural Relation Extraction 2020 ·Hao Peng, Tianyu Gao, Xu Han, Yankai Lin, Peng Li, Zhiyuan Liu, Maosong Sun, Jie Zhou	113
18	Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting breakdown → 2020 ·Information Sciences ·Hao Peng, (unknown), Bowen Du, Md Zakirul Alam Bhuiyan, Hongyuan Ma, Jianwei Liu, Lihong Wang, Zeyu Yang, Linfeng Du, Senzhang Wang, Philip S. Yu	243
19	Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification 2019 ·IEEE Transactions on Knowledge and Data Engineering ·Hao Peng, Jianxin Li, Senzhang Wang, Lihong Wang, Qiran Gong, Renyu Yang, Bo Li, Philip S. Yu, Lifang He	124
20	Towards a distributed local-search approach for partitioning large-scale social networks 2019 ·Information Sciences ·(unknown), (unknown), Jing Li, (unknown), C. H. Chang, Bo Li, (unknown), Hao Peng	6

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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