Songyu Ke

766 total citations · 1 hit paper
8 papers, 533 citations indexed

About

Songyu Ke is a scholar working on Signal Processing, Building and Construction and Artificial Intelligence. According to data from OpenAlex, Songyu Ke has authored 8 papers receiving a total of 533 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Signal Processing, 5 papers in Building and Construction and 3 papers in Artificial Intelligence. Recurrent topics in Songyu Ke's work include Traffic Prediction and Management Techniques (5 papers), Data Management and Algorithms (3 papers) and Human Mobility and Location-Based Analysis (3 papers). Songyu Ke is often cited by papers focused on Traffic Prediction and Management Techniques (5 papers), Data Management and Algorithms (3 papers) and Human Mobility and Location-Based Analysis (3 papers). Songyu Ke collaborates with scholars based in China and Singapore. Songyu Ke's co-authors include Junbo Zhang, Yuxuan Liang, Yu Zheng, Xiuwen Yi, Zheyi Pan, Roger Zimmermann, Yiwei Wang, Qingsong Wen, Yong Yu and Yu Zheng and has published in prestigious journals such as Artificial Intelligence, IEEE Transactions on Knowledge and Data Engineering and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Songyu Ke

7 papers receiving 521 citations

Hit 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.

GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction

2018 371 citations Yuxuan Liang, Songyu Ke et al. profile →

Peers

Songyu Ke

BC

TRANS

EE

SP

AI

Jin Fan China

Lyuchao Liao China

Dewen Seng China

Youru Li China

Deqiang Kong China

Manuel Méndez Spain

Liangzhe Han China

Shouxu Jiang China

Chunlu Wang China

Jin Fan China

Songyu Ke

164 ×0.6

BC

114 ×0.7

TRANS

119 ×0.8

EE

87 ×0.6

SP

175 ×1.7

AI

Citations per year, relative to Songyu Ke Songyu Ke (= 1×) peers Jin Fan

Countries citing papers authored by Songyu Ke

Since Specialization

Citations

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

Fields of papers citing papers by Songyu Ke

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Songyu Ke

This figure shows the co-authorship network connecting the top 25 collaborators of Songyu Ke. A scholar is included among the top collaborators of Songyu Ke 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 Songyu Ke. Songyu Ke 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:

8 of 8 papers shown

1.

Ke, Songyu, et al.. (2024). VQGG: Generating Adaptive Graphs for Traffic Forecasting via a Vector-Quantized Graph Generator. 1–8. 1 indexed citations

2.

Ke, Songyu, Zheyi Pan, Tianfu He, et al.. (2023). AutoSTG+: An automatic framework to discover the optimal network for spatio-temporal graph prediction. Artificial Intelligence. 318. 103899–103899. 12 indexed citations

3.

Liang, Yuxuan, Songyu Ke, Yiwei Wang, et al.. (2023). AirFormer: Predicting Nationwide Air Quality in China with Transformers. Proceedings of the AAAI Conference on Artificial Intelligence. 37(12). 14329–14337. 73 indexed citations

4.

Ke, Songyu, et al.. (2022). Efficient Spatio-Temporal Randomly Wired Neural Networks for Traffic Forecasting. 28. 1–8.

5.

Yi, Xiuwen, Yanyong Huang, Songyu Ke, et al.. (2021). Gas-Theft Suspect Detection Among Boiler Room Users: A Data-Driven Approach. IEEE Transactions on Knowledge and Data Engineering. 34(12). 5796–5808. 6 indexed citations

6.

Ke, Songyu, et al.. (2021). Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 35(5). 4312–4319. 14 indexed citations

7.

Pan, Zheyi, Songyu Ke, Yuxuan Liang, et al.. (2021). AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph✱. 1846–1855. 56 indexed citations

8.

Liang, Yuxuan, Songyu Ke, Junbo Zhang, Xiuwen Yi, & Yu Zheng. (2018). GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction. 3428–3434. 371 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.

Explore authors with similar magnitude of impact