Shanshan Qin

1.6k total citations
36 papers, 1.2k citations indexed

About

Shanshan Qin is a scholar working on Electrical and Electronic Engineering, Environmental Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Shanshan Qin has authored 36 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 9 papers in Environmental Engineering and 7 papers in Cellular and Molecular Neuroscience. Recurrent topics in Shanshan Qin's work include Energy Load and Power Forecasting (7 papers), Neurobiology and Insect Physiology Research (6 papers) and Electric Power System Optimization (5 papers). Shanshan Qin is often cited by papers focused on Energy Load and Power Forecasting (7 papers), Neurobiology and Insect Physiology Research (6 papers) and Electric Power System Optimization (5 papers). Shanshan Qin collaborates with scholars based in China, United States and Canada. Shanshan Qin's co-authors include Jianzhou Wang, Feng Liu, Haiyan Jiang, Qingping Zhou, Yiliao Song, Tiejun Liu, Dujian Zou, Andrey P. Jivkov, Jiansheng Qu and Jie Wu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Neuroscience.

In The Last Decade

Shanshan Qin

34 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shanshan Qin China 17 423 291 182 169 148 36 1.2k
Nathan Downs Australia 21 257 0.6× 352 1.2× 316 1.7× 52 0.3× 19 0.1× 101 1.7k
Giovanni Barone Italy 28 656 1.6× 403 1.4× 92 0.5× 149 0.9× 99 0.7× 72 2.5k
Yueqing Li China 30 397 0.9× 252 0.9× 153 0.8× 34 0.2× 22 0.1× 149 2.8k
Takahiro Yoshida Japan 19 336 0.8× 178 0.6× 147 0.8× 26 0.2× 17 0.1× 81 1.3k
Ashutosh Mishra India 22 188 0.4× 106 0.4× 132 0.7× 16 0.1× 22 0.1× 119 1.5k
Zhongyi Wang China 22 460 1.1× 267 0.9× 65 0.4× 56 0.3× 41 0.3× 89 1.3k
Zhe Song China 19 158 0.4× 208 0.7× 169 0.9× 19 0.1× 34 0.2× 52 902
Dong Chen China 23 96 0.2× 930 3.2× 39 0.2× 120 0.7× 224 1.5× 130 1.8k
Zhi Zhang China 16 410 1.0× 53 0.2× 61 0.3× 23 0.1× 34 0.2× 105 1.0k
Youngdeok Hwang United States 13 276 0.7× 108 0.4× 64 0.4× 43 0.3× 6 0.0× 39 996

Countries citing papers authored by Shanshan Qin

Since Specialization
Citations

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

Fields of papers citing papers by Shanshan Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanshan Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Shanshan Qin. A scholar is included among the top collaborators of Shanshan Qin 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 Shanshan Qin. Shanshan Qin 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.
Lee, James, et al.. (2025). Decision-Making Framework for Marine Anchor Selection in Floating Offshore Wind Farms. Offshore Technology Conference. 1 indexed citations
2.
Qin, Shanshan, et al.. (2024). One Nose but Two Nostrils: Learning to Align with Sparse Connections between Two Olfactory Cortices. PubMed. 2(4). 1 indexed citations
3.
Zou, Dujian, et al.. (2024). Mechanistic insights into two-stage expansion of concrete under external sulfate attack. Construction and Building Materials. 446. 138027–138027. 17 indexed citations
4.
Zhang, Ming, Shanshan Qin, Hanxiong Lyu, et al.. (2023). A transport-chemical-physical–mechanical model for concrete subjected to external sulfate attack and drying–wetting cycles. Engineering Fracture Mechanics. 293. 109726–109726. 18 indexed citations
5.
Lin, Albert, Shanshan Qin, Min Wu, et al.. (2023). Functional imaging and quantification of multineuronal olfactory responses in C. elegans. Science Advances. 9(9). eade1249–eade1249. 19 indexed citations
6.
Qin, Shanshan, et al.. (2023). Coordinated drift of receptive fields in Hebbian/anti-Hebbian network models during noisy representation learning. Nature Neuroscience. 26(2). 339–349. 19 indexed citations
7.
Jiang, Haiyan, Shanshan Qin, & Oscar Hernán Madrid Padilla. (2022). Feature grouping and sparse principal component analysis with truncated regularization. Stat. 12(1).
8.
Yuan, Yuan, Huixia Ren, Yanjun Li, et al.. (2022). Cell-to-cell variability in inducible Caspase9-mediated cell death. Cell Death and Disease. 13(1). 34–34. 8 indexed citations
9.
Liu, Yuxuan, et al.. (2021). Short-Term Plasticity Regulates Both Divisive Normalization and Adaptive Responses in Drosophila Olfactory System. Frontiers in Computational Neuroscience. 15. 730431–730431. 2 indexed citations
10.
Vogt, Katrin, Matthias Schlichting, Luis Hernandez-Nunez, et al.. (2021). Internal state configures olfactory behavior and early sensory processing in Drosophila larvae. Science Advances. 7(1). 47 indexed citations
11.
Qin, Shanshan, et al.. (2021). Contrastive Similarity Matching for Supervised Learning. Neural Computation. 33(5). 1300–1328. 4 indexed citations
12.
Qin, Shanshan, et al.. (2018). Network Motifs Capable of Decoding Transcription Factor Dynamics. Scientific Reports. 8(1). 3594–3594. 10 indexed citations
13.
Qin, Shanshan & Chao Tang. (2018). Early-warning signals of critical transition: Effect of extrinsic noise. Physical review. E. 97(3). 32406–32406. 13 indexed citations
14.
Wang, Jianzhou, Haiyan Jiang, Qingping Zhou, Jie Wu, & Shanshan Qin. (2015). China’s natural gas production and consumption analysis based on the multicycle Hubbert model and rolling Grey model. Renewable and Sustainable Energy Reviews. 53. 1149–1167. 101 indexed citations
15.
Qin, Shanshan, Jianzhou Wang, Jie Wu, & Ge Zhao. (2015). A hybrid model based on smooth transition periodic autoregressive and Elman artificial neural network for wind speed forecasting of the Hebei region in China. International Journal of Green Energy. 13(6). 595–607. 16 indexed citations
16.
Chen, Xuejun, et al.. (2015). Short-Term Wind Speed Forecasting Study and Its Application Using a Hybrid Model Optimized by Cuckoo Search. Mathematical Problems in Engineering. 2015. 1–18. 13 indexed citations
17.
Qu, Jiansheng, Shanshan Qin, Lina Liu, Jingjing Zeng, & Yue Bian. (2015). A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China. Environmental Science and Pollution Research. 23(7). 6430–6442. 13 indexed citations
18.
Wang, Jianzhou, et al.. (2014). Swarm Intelligence‐Based Hybrid Models for Short‐Term Power Load Prediction. Mathematical Problems in Engineering. 2014(1). 17 indexed citations
19.
Han, Yujun, Shanshan Qin, & Susan R. Wessler. (2013). Comparison of class 2 transposable elements at superfamily resolution reveals conserved and distinct features in cereal grass genomes. BMC Genomics. 14(1). 71–71. 49 indexed citations
20.
Tang, Shaoqiang, Shanshan Qin, & R. O. Weber. (1993). Numerical studies on 2-dimensional reaction-diffusion equations. The Journal of the Australian Mathematical Society Series B Applied Mathematics. 35(2). 223–243. 11 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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