Shiyu Liang

2.0k total citations
20 papers, 221 citations indexed

About

Shiyu Liang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Shiyu Liang has authored 20 papers receiving a total of 221 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Molecular Biology. Recurrent topics in Shiyu Liang's work include Neural Networks and Applications (4 papers), Stochastic Gradient Optimization Techniques (4 papers) and Advanced Neural Network Applications (3 papers). Shiyu Liang is often cited by papers focused on Neural Networks and Applications (4 papers), Stochastic Gradient Optimization Techniques (4 papers) and Advanced Neural Network Applications (3 papers). Shiyu Liang collaborates with scholars based in China, United States and France. Shiyu Liang's co-authors include Jiawei Luo, R. Srikant, Ramakrishnan Srikant, Yixuan Li, Ruoyu Sun, Tian Ding, Jason D. Lee, Shuai Lü, Rui‐tian Liu and Xiaolin Yu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and PLoS ONE.

In The Last Decade

Shiyu Liang

18 papers receiving 208 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shiyu Liang China 9 90 55 32 13 11 20 221
Wenwen Min China 9 47 0.5× 150 2.7× 53 1.7× 10 0.8× 13 1.2× 48 294
Andrei Doncescu France 7 53 0.6× 63 1.1× 48 1.5× 5 0.4× 12 1.1× 56 204
Md. Mohaiminul Islam Bangladesh 9 43 0.5× 67 1.2× 33 1.0× 6 0.5× 31 2.8× 28 206
Andrew Jones United States 4 51 0.6× 104 1.9× 15 0.5× 10 0.8× 5 0.5× 9 213
Long Pang China 10 33 0.4× 112 2.0× 23 0.7× 7 0.5× 21 1.9× 44 311
Meijing Li China 9 76 0.8× 110 2.0× 13 0.4× 3 0.2× 19 1.7× 26 287
Ruijia Li China 12 55 0.6× 114 2.1× 29 0.9× 13 1.0× 31 2.8× 39 371
Masayuki Kobayashi Japan 10 75 0.8× 39 0.7× 38 1.2× 10 0.8× 8 0.7× 35 310

Countries citing papers authored by Shiyu Liang

Since Specialization
Citations

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

Fields of papers citing papers by Shiyu Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shiyu Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Shiyu Liang. A scholar is included among the top collaborators of Shiyu Liang 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 Shiyu Liang. Shiyu Liang 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.
Liang, Shiyu. (2025). Enhancing the reliability of out-of-distribution image detection in neural networks. International Conference on Learning Representations. 12 indexed citations
2.
Lü, Bin, Xiaoying Gan, Shiyu Liang, et al.. (2024). Graph Out-of-Distribution Generalization With Controllable Data Augmentation. IEEE Transactions on Knowledge and Data Engineering. 36(11). 6317–6329. 3 indexed citations
3.
Liang, Hongyu, Jingya Wang, Hongbin Zhang, et al.. (2024). PDGPT: A large language model for acquiring phase diagram information in magnesium alloys. SHILAP Revista de lepidopterología. 2(4). 7 indexed citations
4.
Liang, Shiyu, Yue Zhang, Liting Lyu, Shuang Wang, & Zongbao K. Zhao. (2023). Secretory expression of β-1,3-glucomannanase in the oleaginous yeast Rhodosporidium toruloides for improved lipid extraction. Bioresources and Bioprocessing. 10(1). 16–16. 7 indexed citations
5.
Liao, Liuwen, et al.. (2023). Applicability of photovoltaic panel rainwater harvesting system in improving water-energy-food nexus performance in semi-arid areas. The Science of The Total Environment. 896. 164938–164938. 14 indexed citations
6.
Liang, Shiyu, et al.. (2023). A predicted structure of NADPH Oxidase 1 identifies key components of ROS generation and strategies for inhibition. PLoS ONE. 18(5). e0285206–e0285206. 4 indexed citations
7.
Fu, Luoyi, Shiyu Liang, Xinbing Wang, et al.. (2023). Hi-PART: Going Beyond Graph Pooling with Hierarchical Partition Tree for Graph-Level Representation Learning. ACM Transactions on Knowledge Discovery from Data. 18(4). 1–20. 1 indexed citations
8.
Lü, Bin, Xiaoying Gan, Shiyu Liang, et al.. (2023). DataExpo: A One-Stop Dataset Service for Open Science Research. 32–36.
9.
Liang, Shiyu, et al.. (2023). Neuronal conversion from glia to replenish the lost neurons. Neural Regeneration Research. 19(7). 1446–1453. 17 indexed citations
10.
Belambri, Sahra Amel, Viviana Marzaioli, Margarita Hurtado-Nédelec, et al.. (2022). Impaired p47phox phosphorylation in neutrophils from patients with p67phox-deficient chronic granulomatous disease. Blood. 139(16). 2512–2522. 12 indexed citations
11.
Liang, Shiyu, Ruoyu Sun, & R. Srikant. (2022). Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity. SIAM Journal on Optimization. 32(4). 2797–2827. 3 indexed citations
12.
Liang, Shiyu, et al.. (2022). Psychological and Emotional Responses during Different Stages of the COVID-19 Pandemic Based on a Survey of a Mental Health Hotline. International Journal of Mental Health Promotion. 24(5). 711–724. 3 indexed citations
13.
Sun, Ruoyu, et al.. (2020). The Global Landscape of Neural Networks: An Overview. IEEE Signal Processing Magazine. 37(5). 95–108. 35 indexed citations
14.
Gupta, Harsh, et al.. (2020). The Role of Regularization in Overparameterized Neural Networks. 4683–4688. 3 indexed citations
15.
Liang, Shiyu, Ruoyu Sun, Yixuan Li, & R. Srikant. (2018). Understanding the Loss Surface of Neural Networks for Binary Classification. International Conference on Machine Learning. 2835–2843. 1 indexed citations
16.
Fu, Luoyi, et al.. (2018). FINE: A Framework for Distributed Learning on Incomplete Observations for Heterogeneous Crowdsensing Networks. IEEE/ACM Transactions on Networking. 26(3). 1092–1109. 6 indexed citations
17.
Liang, Shiyu, Ruoyu Sun, Jason D. Lee, & R. Srikant. (2018). Adding One Neuron Can Eliminate All Bad Local Minima. arXiv (Cornell University). 31. 4355–4365. 15 indexed citations
18.
Liang, Shiyu, Yixuan Li, & Ramakrishnan Srikant. (2017). Principled Detection of Out-of-Distribution Examples in Neural Networks.. arXiv (Cornell University). 35 indexed citations
19.
Liang, Shiyu & R. Srikant. (2016). Why Deep Neural Networks. arXiv (Cornell University). 8 indexed citations
20.
Luo, Jiawei & Shiyu Liang. (2014). Prioritization of potential candidate disease genes by topological similarity of protein–protein interaction network and phenotype data. Journal of Biomedical Informatics. 53. 229–236. 35 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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