Hanghang Tong

17.7k total citations · 5 hit papers
327 papers, 10.5k citations indexed

About

Hanghang Tong is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hanghang Tong has authored 327 papers receiving a total of 10.5k indexed citations (citations by other indexed papers that have themselves been cited), including 213 papers in Artificial Intelligence, 122 papers in Statistical and Nonlinear Physics and 87 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hanghang Tong's work include Advanced Graph Neural Networks (128 papers), Complex Network Analysis Techniques (118 papers) and Topic Modeling (45 papers). Hanghang Tong is often cited by papers focused on Advanced Graph Neural Networks (128 papers), Complex Network Analysis Techniques (118 papers) and Topic Modeling (45 papers). Hanghang Tong collaborates with scholars based in United States, China and Hong Kong. Hanghang Tong's co-authors include Christos Faloutsos, Si Zhang, Leman Akoglu, Jia-Yu Pan, Danai Koutra, Ross Maciejewski, Jiejun Xu, Tina Eliassi‐Rad, Jingrui He and Changshui Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Proceedings of the IEEE and Communications of the ACM.

In The Last Decade

Hanghang Tong

314 papers receiving 10.2k 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.

Graph convolutional networks: a comprehensive review

2019 1.0k citations Hanghang Tong, Jiejun Xu et al. profile →
Graph based anomaly detection and description: a survey

2014 878 citations Leman Akoglu, Hanghang Tong et al. profile →
Fast Random Walk with Restart and Its Applications

2006 820 citations Hanghang Tong, Christos Faloutsos et al. profile →
Activity recognition with smartphone sensors

2014 296 citations Hanghang Tong et al. profile →
Data Augmentation for Deep Graph Learning

2022 128 citations Zhe Xu, Hanghang Tong et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hanghang Tong United States	47	5.7k	3.3k	2.6k	2.1k	1.9k	327	10.5k
Wenwu Zhu China	55	7.1k 1.2×	3.4k 1.0×	4.2k 1.6×	2.5k 1.2×	3.3k 1.7×	410	13.9k
Peng Cui China	48	7.1k 1.2×	3.7k 1.1×	2.2k 0.8×	2.5k 1.2×	1.2k 0.6×	219	10.4k
Yizhou Sun United States	44	7.2k 1.3×	3.5k 1.1×	1.3k 0.5×	3.6k 1.7×	1.6k 0.9×	206	10.5k
Hongyuan Zha United States	57	6.2k 1.1×	2.0k 0.6×	4.1k 1.6×	3.3k 1.6×	1.2k 0.7×	325	13.3k
Shirui Pan Australia	52	7.5k 1.3×	1.7k 0.5×	2.0k 0.8×	1.7k 0.8×	1.1k 0.6×	303	12.8k
Lise Getoor United States	48	6.2k 1.1×	2.2k 0.7×	1.0k 0.4×	2.0k 1.0×	1.3k 0.7×	234	9.0k
Xueqi Cheng China	52	7.2k 1.3×	2.5k 0.8×	1.5k 0.6×	3.4k 1.6×	1.3k 0.7×	517	11.6k
Aristides Gionis Finland	50	5.5k 1.0×	2.6k 0.8×	2.9k 1.1×	3.5k 1.6×	2.6k 1.4×	200	11.7k
Maosong Sun China	59	14.1k 2.5×	1.8k 0.6×	2.7k 1.0×	2.8k 1.3×	912 0.5×	359	18.2k
Li Zhang China	44	3.3k 0.6×	1.3k 0.4×	3.3k 1.2×	1.4k 0.6×	604 0.3×	485	9.2k

Countries citing papers authored by Hanghang Tong

Since Specialization

Citations

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

Fields of papers citing papers by Hanghang Tong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanghang Tong

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

Kang, SeongKu, et al.. (2025). Continual Recommender Systems. 6857–6860.

2.

Zhu, Yada, Kinh Tieu, Onkar Bhardwaj, et al.. (2025). ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method. 6367–6371.

3.

Wu, Bang Ye, et al.. (2024). Trustworthy Graph Neural Networks: Aspects, Methods, and Trends. Proceedings of the IEEE. 112(2). 97–139. 44 indexed citations

4.

Wu, Jun, Jingrui He, & Hanghang Tong. (2024). Distributional Network of Networks for Modeling Data Heterogeneity. 3379–3390.

5.

Sun, Chenkai, et al.. (2024). Large Language Model-Guided Disentangled Belief Representation Learning on Polarized Social Graphs. 1–9. 2 indexed citations

6.

Tong, Hanghang, et al.. (2024). Fairgen: Towards Fair Graph Generation. 2285–2297. 1 indexed citations

7.

Kang, Jian, et al.. (2024). Ensuring User-side Fairness in Dynamic Recommender Systems. 3667–3678. 8 indexed citations

8.

Ying, Lei, et al.. (2023). Reconstructing Graph Diffusion History from a Single Snapshot. 1978–1988.

9.

Xu, Zhe, et al.. (2023). Kernel Ridge Regression-Based Graph Dataset Distillation. 2850–2861. 20 indexed citations

10.

Liu, Lihui, et al.. (2022). ABM: Attention-based Message Passing Network for Knowledge Graph Completion. 2022 IEEE International Conference on Big Data (Big Data). 26. 339–348. 1 indexed citations

11.

Ma, Shuai, et al.. (2022). Mobility Inference on Long-Tailed Sparse Trajectory. ACM Transactions on Intelligent Systems and Technology. 14(1). 1–26. 1 indexed citations

12.

Jing, Baoyu, et al.. (2021). SODA: Detecting COVID-19 in Chest X-Rays With Semi-Supervised Open Set Domain Adaptation. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(5). 2605–2612. 38 indexed citations

13.

Shi, Lei, Qi Liao, Hanghang Tong, et al.. (2020). OnionGraph: Hierarchical topology+attribute multivariate network visualization. Visual Informatics. 4(1). 43–57. 7 indexed citations

14.

Yao, Yuan, et al.. (2018). Bug Localization via Supervised Topic Modeling. 607–616. 12 indexed citations

15.

Yao, Yuan, et al.. (2015). Ice-breaking: mitigating cold-start recommendation problem by rating comparison. International Conference on Artificial Intelligence. 3981–3987. 20 indexed citations

16.

Chen, Zhe, Hanghang Tong, & Lei Ying. (2015). Full diffusion history reconstruction in networks. 707–716. 4 indexed citations

17.

Yao, Yuan, Hanghang Tong, Tao Xie, et al.. (2014). Joint voting prediction for questions and answers in CQA. 340–343. 8 indexed citations

18.

Tong, Hanghang, et al.. (2011). Non-Negative Residual Matrix Factorization with Application to Graph Anomaly Detection. 143–153. 69 indexed citations

19.

Chau, Duen Horng, Christos Faloutsos, Hanghang Tong, et al.. (2008). GRAPHITE: A Visual Query System for Large Graphs. 963–966. 34 indexed citations

20.

Tong, Hanghang, Huiming Qu, & Hani Jamjoom. (2008). Measuring Proximity on Graphs with Side Information. 598–607. 7 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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