Peng Cui

20.8k total citations · 6 hit papers
219 papers, 10.4k citations indexed

About

Peng Cui is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Peng Cui has authored 219 papers receiving a total of 10.4k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Artificial Intelligence, 68 papers in Computer Vision and Pattern Recognition and 56 papers in Statistical and Nonlinear Physics. Recurrent topics in Peng Cui's work include Complex Network Analysis Techniques (56 papers), Advanced Graph Neural Networks (52 papers) and Recommender Systems and Techniques (36 papers). Peng Cui is often cited by papers focused on Complex Network Analysis Techniques (56 papers), Advanced Graph Neural Networks (52 papers) and Recommender Systems and Techniques (36 papers). Peng Cui collaborates with scholars based in China, United States and Canada. Peng Cui's co-authors include Wenwu Zhu, Daixin Wang, Ziwei Zhang, Jian Pei, Shiqiang Yang, Xiao Wang, Mingdong Ou, Meng Jiang, Christos Faloutsos and Zheyan Shen and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Environmental Pollution.

In The Last Decade

Peng Cui

198 papers receiving 10.1k 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.

Structural Deep Network Embedding

2016 1.7k citations Daixin Wang, Peng Cui et al. profile →
Deep Learning on Graphs: A Survey

2020 949 citations Ziwei Zhang, Peng Cui et al. IEEE Transactions on Knowledge and Data Engineering profile →
A Survey on Network Embedding

2018 791 citations Peng Cui, Xiao Wang et al. IEEE Transactions on Knowledge and Data Engineering profile →
Asymmetric Transitivity Preserving Graph Embedding

2016 716 citations Mingdong Ou, Peng Cui et al. profile →
Community Preserving Network Embedding

2017 565 citations Xiao Wang, Peng Cui et al. profile →
Stable learning establishes some common ground between causal inference and machine learning

2022 131 citations Peng Cui et al. profile →

Peers

Countries citing papers authored by Peng Cui

Since Specialization

Citations

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

Fields of papers citing papers by Peng Cui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peng Cui

This figure shows the co-authorship network connecting the top 25 collaborators of Peng Cui. A scholar is included among the top collaborators of Peng Cui 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 Cui. Peng Cui 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	Moving to wheat‐farming regions increases analytic thought, but moving to cities does not: A three‐wave longitudinal study 2025 ·British Journal of Psychology ·Alexander Scott English, Thomas Talhelm, (unknown), Liuqing Wei, (unknown), Jianhong Ma, Haitao Yu, (unknown), (unknown), Tianhai Lin, Meng Zhang, Lijuan Hu, Peng Cui, (unknown), (unknown), (unknown), Zhijia Zeng, (unknown), (unknown)	0
2	A Robust Deep Q-Network (DQN) for Heterogeneous Tasks and QoS-Aware UAV Relay Communication Optimization 2025 ·IEEE Internet of Things Journal ·(unknown), Peng Cui, Liming Jiang, Ke Nai, Wei Liang, Jin Wang, Kuan‐Ching Li, Al‐Sakib Khan Pathan	0
3	On the Out-Of-Distribution Generalization of Large Multimodal Models 2025 ·(unknown), (unknown), (unknown), (unknown), Renzhe Xu, Yuqing Yang, (unknown), (unknown), Liping Jing, Peng Cui	1
4	Stepwise Attention-Guided Multiscale Fusion Network for Lightweight and High-Accurate SAR Ship Detection 2024 ·Remote Sensing ·Chunyuan Wang, (unknown), Fei Wu, Peng Cui, (unknown), Ye Zhang	2
5	Inductive Meta-Path Learning for Schema-Complex Heterogeneous Information Networks 2024 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·(unknown), (unknown), Kewei Cheng, Yunfei Wang, Peng Cui, Yizhou Sun, Zhong Liu	4
6	AI for Education (AI4EDU): Advancing Personalized Education with LLM and Adaptive Learning 2024 ·Qingsong Wen, (unknown), Carles Sierra, Rose Luckin, (unknown), Zitao Liu, Peng Cui, Jiliang Tang	15
7	A Data-Driven Decision Support Framework for Player Churn Analysis in Online Games 2023 ·(unknown), Runze Wu, Shiwei Zhao, Jianrong Tao, (unknown), (unknown), Changjie Fan, Peng Cui	4
8	GRASS: Learning Spatial–Temporal Properties From Chainlike Cascade Data for Microscopic Diffusion Prediction 2023 ·IEEE Transactions on Neural Networks and Learning Systems ·(unknown), Chunhe Xia, Tianbo Wang, (unknown), Peng Cui, (unknown)	59
9	Generalizing Graph Neural Networks on Out-of-Distribution Graphs 2023 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang	48
10	Intention-Aware Sequential Recommendation With Structured Intent Transition 2021 ·IEEE Transactions on Knowledge and Data Engineering ·Haoyang Li, Xin Wang, Ziwei Zhang, Jianxin Ma, Peng Cui, Wenwu Zhu	46
11	Integrated Latent Heterogeneity and Invariance Learning in Kernel Space 2021 ·Neural Information Processing Systems ·Jiashuo Liu, Zheyuan Hu, Peng Cui, Бо Ли, Zheyan Shen	0
12	Improving Accuracy and Diversity in Matching of Recommendation With Diversified Preference Network 2021 ·IEEE Transactions on Big Data ·Ruobing Xie, (unknown), Shukai Liu, Ziwei Zhang, Peng Cui, Bo Zhang, Leyu Lin	29
13	Counterfactual Prediction for Bundle Treatment 2020 ·Neural Information Processing Systems ·Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He	13
14	Continuous Treatment Effect Estimation via Generative Adversarial De-confounding. 2020 ·Knowledge Discovery and Data Mining ·Yunzhe Li, Kun Kuang, Bo Li, Peng Cui, Jianrong Tao, Hongxia Yang, Fei Wu	2
15	The General Black-box Attack Method for Graph Neural Networks. 2019 ·arXiv (Cornell University) ·Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, Junzhou Huang	3
16	Disentangled Graph Convolutional Networks 2019 ·International Conference on Machine Learning ·Jianxin Ma, Peng Cui, Kun Kuang, Xin Wang, Wenwu Zhu	75
17	Catching Synchronized Behaviors in Large Networks 2016 ·ACM Transactions on Knowledge Discovery from Data ·Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang	53
18	Deep multimodal hashing with orthogonal regularization 2015 ·International Conference on Artificial Intelligence ·Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu	74
19	The ARM9-based Design of the Fingerprint Identification System 2010 ·Peng Cui	1
20	Dynamic Retrieval in an Urban Contextual Databank System using Java-CGI Communications. Development of the SUCoD Prototype 2001 ·Peng Cui, (unknown), (unknown), Barry Lawson	2

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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