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.
Learning Laplacian Matrix in Smooth Graph Signal Representations
2016362 citationsXiaowen Dong, Dorina Thanou et al.IEEE Transactions on Signal Processingprofile →
Learning Graphs From Data: A Signal Representation Perspective
2019249 citationsXiaowen Dong, Dorina Thanou et al.IEEE Signal Processing Magazineprofile →
Mobility patterns are associated with experienced income segregation in large US cities
2021150 citationsEsteban Moro, Dan Calacci et al.Nature Communicationsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Xiaowen Dong'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 Xiaowen Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaowen Dong more than expected).
This network shows the impact of papers produced by Xiaowen Dong. 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 Xiaowen Dong. The network helps show where Xiaowen Dong may publish in the future.
Co-authorship network of co-authors of Xiaowen Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaowen Dong.
A scholar is included among the top collaborators of Xiaowen Dong 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 Xiaowen Dong. Xiaowen Dong is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Osborne, Michael A., et al.. (2021). Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. Neural Information Processing Systems. 34.2 indexed citations
8.
Moro, Esteban, Dan Calacci, Xiaowen Dong, & Alex Pentland. (2021). Mobility patterns are associated with experienced income segregation in large US cities. Nature Communications. 12(1). 4633–4633.150 indexed citations breakdown →
9.
Thanou, Dorina, et al.. (2021). Interpretable Stability Bounds for Spectral Graph Filters. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 139. 5388–5397.5 indexed citations
Toni, Laura, et al.. (2020). Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis.. UCL Discovery (University College London). 3133–3143.1 indexed citations
13.
Leng, Yan, Xiaowen Dong, Junfeng Wu, & Alex Pentland. (2020). Learning quadratic games on networks. Oxford University Research Archive (ORA) (University of Oxford).3 indexed citations
14.
Dong, Xiaowen, Dorina Thanou, Michael Rabbat, & Pascal Frossard. (2019). Learning Graphs From Data: A Signal Representation Perspective. IEEE Signal Processing Magazine. 36(3). 44–63.249 indexed citations breakdown →
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.