Yao Ma

6.7k total citations · 3 hit papers
76 papers, 3.4k citations indexed

About

Yao Ma is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yao Ma has authored 76 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Artificial Intelligence, 16 papers in Information Systems and 16 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yao Ma's work include Advanced Graph Neural Networks (34 papers), Complex Network Analysis Techniques (14 papers) and Topic Modeling (11 papers). Yao Ma is often cited by papers focused on Advanced Graph Neural Networks (34 papers), Complex Network Analysis Techniques (14 papers) and Topic Modeling (11 papers). Yao Ma collaborates with scholars based in United States, China and Hong Kong. Yao Ma's co-authors include Jiliang Tang, Wenqi Fan, Qing Li, Dawei Yin, Eric Zhao, Yuan He, Wei Jin, Suhang Wang, Tyler Derr and Xiaorui Liu and has published in prestigious journals such as IEEE Access, Sensors and IEEE Transactions on Vehicular Technology.

In The Last Decade

Yao Ma

68 papers receiving 3.3k citations

Hit Papers

Graph Neural Networks for Social Recommendation 2019 2026 2021 2023 2019 2020 2020 250 500 750 1000
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.

  1. Graph Neural Networks for Social Recommendation
    2019 1.1k citations Wenqi Fan, Yao Ma et al. profile →
  2. Traffic Flow Prediction via Spatial Temporal Graph Neural Network
    2020 383 citations Yao Ma, Wei Jin et al. profile →
  3. Graph Structure Learning for Robust Graph Neural Networks
    2020 362 citations Wei Jin, Yao Ma et al. profile →

Peers

Yao Ma
Chao Huang China
Tong Chen China
Fuzhen Zhuang China
Dongjin Song United States
Shaojie Qiao China
Jin Huang China
Ziyu Guan China
Bryan Hooi Singapore
Dawei Yin China
Rongfang Bie China
Chao Huang China
Yao Ma
Citations per year, relative to Yao Ma Yao Ma (= 1×) peers Chao Huang

Countries citing papers authored by Yao Ma

Since Specialization
Citations

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

Fields of papers citing papers by Yao Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yao Ma

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

All Works

20 of 20 papers shown
1.
Zhang, Liangliang, et al.. (2025). Learning to Reduce the Scale of Large Graphs: A Comprehensive Survey. ACM Transactions on Knowledge Discovery from Data. 19(5). 1–25.
2.
Li, Fangting, Xiaoyue Zhang, Bin Lv, et al.. (2025). Deep learning-based anterior segment identification and parameter assessment of primary angle closure disease in ultrasound biomicroscopy images. BMJ Open Ophthalmology. 10(1). e001600–e001600. 1 indexed citations
3.
He, Qi, et al.. (2025). A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness. ACM Transactions on Intelligent Systems and Technology. 16(6). 1–87. 3 indexed citations
4.
5.
Jin, Wei, Haohan Wang, Daochen Zha, et al.. (2024). DCAI: Data-centric Artificial Intelligence. 1482–1485. 2 indexed citations
6.
Wang, Lin, Wenqi Fan, Jiatong Li, Yao Ma, & Qing Li. (2024). Fast Graph Condensation with Structure-based Neural Tangent Kernel. 4439–4448. 13 indexed citations
7.
Chen, Yongle, et al.. (2024). Causal Inference-Based Adversarial Domain Adaptation for Cross-Domain Industrial Intrusion Detection. IEEE Transactions on Industrial Informatics. 21(1). 970–979. 4 indexed citations
8.
Fan, Wenqi, Xiangyu Zhao, Qing Li, et al.. (2023). Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles. IEEE Transactions on Knowledge and Data Engineering. 35(12). 12415–12429. 15 indexed citations
9.
Jin, Wei, et al.. (2023). Learning Representations for Hyper-Relational Knowledge Graphs. 253–257. 7 indexed citations
10.
Xingkui, Wang, et al.. (2023). IoT Device Identification Method Based on Causal Inference. Electronics. 12(12). 2727–2727. 2 indexed citations
11.
Liu, Xiaorui, Wei Jin, Han Xu, et al.. (2021). Graph Neural Networks with Adaptive Residual. Neural Information Processing Systems. 34. 16 indexed citations
12.
Fan, Wenqi, Tyler Derr, Xiangyu Zhao, et al.. (2021). Attacking Black-box Recommendations via Copying Cross-domain User Profiles. 1583–1594. 54 indexed citations
13.
Fan, Wenqi, Yao Ma, Qing Li, et al.. (2020). A Graph Neural Network Framework for Social Recommendations. IEEE Transactions on Knowledge and Data Engineering. 34(5). 2033–2047. 142 indexed citations
14.
Ma, Yao, et al.. (2020). Graph Pooling with Representativeness. 302–311. 9 indexed citations
15.
Xiang, Jie, Jiayue Xue, Hao Guo, et al.. (2019). Graph-based network analysis of resting-state fMRI: test-retest reliability of binarized and weighted networks. Brain Imaging and Behavior. 14(5). 1361–1372. 18 indexed citations
16.
Ma, Yao, Ziyi Guo, Zhaochun Ren, et al.. (2018). Dynamic Graph Neural Networks. arXiv (Cornell University). 4 indexed citations
17.
Yang, Yanli, Mengni Zhou, Yan Niu, et al.. (2018). Epileptic Seizure Prediction Based on Permutation Entropy. Frontiers in Computational Neuroscience. 12. 55–55. 67 indexed citations
18.
Niu, Gang, Marthinus Christoffel du Plessis, Tomoya Sakai, Yao Ma, & Masashi Sugiyama. (2016). Theoretical comparisons of positive-unlabeled learning against positive-negative learning. neural information processing systems. 29. 1207–1215. 36 indexed citations
19.
Cheng, Jin, Wei Chen, Li Chen, & Yao Ma. (2003). The improvement of genetic algorithm searching performance. 2. 947–951. 7 indexed citations
20.
Ma, Yao. (2000). Spatial analysis of the inbound tourism flow to and in China. Journal of Shaanxi Normal University. 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.

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