Min Shi

2.3k total citations · 1 hit paper
78 papers, 1.6k citations indexed

About

Min Shi is a scholar working on Artificial Intelligence, Information Systems and Electrical and Electronic Engineering. According to data from OpenAlex, Min Shi has authored 78 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 20 papers in Information Systems and 16 papers in Electrical and Electronic Engineering. Recurrent topics in Min Shi's work include Service-Oriented Architecture and Web Services (15 papers), Advanced Graph Neural Networks (11 papers) and Caching and Content Delivery (11 papers). Min Shi is often cited by papers focused on Service-Oriented Architecture and Web Services (15 papers), Advanced Graph Neural Networks (11 papers) and Caching and Content Delivery (11 papers). Min Shi collaborates with scholars based in China, United States and Norway. Min Shi's co-authors include Jianxun Liu, Yufei Tang, Fei Wang, Kangping Li, Tieqiang Wang, Zhao Zhen, Zhiming Xuan, Xingquan Zhu, Yuan Zhuang and Buqing Cao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and Nature Biotechnology.

In The Last Decade

Min Shi

70 papers receiving 1.5k 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.

A day-ahead PV power forecasting method based on LSTM-RNN model and time correlation modification under partial daily pattern prediction framework

2020 483 citations Fei Wang, Tieqiang Wang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Min Shi China	21	831	614	383	268	196	78	1.6k
Sajad Ahmadian Iran	25	988 1.2×	425 0.7×	977 2.6×	65 0.2×	229 1.2×	45	2.0k
Osamu Akashi Japan	17	515 0.6×	811 1.3×	141 0.4×	129 0.5×	1.2k 6.1×	71	2.1k
Ahmed G. Gad Egypt	10	409 0.5×	258 0.4×	354 0.9×	47 0.2×	319 1.6×	13	1.5k
Jiaming Li Australia	18	494 0.6×	415 0.7×	107 0.3×	140 0.5×	183 0.9×	44	1.3k
Mohamed A. Ismail Egypt	20	883 1.1×	146 0.2×	229 0.6×	74 0.3×	125 0.6×	72	1.8k
Sheng-Uei Guan China	20	640 0.8×	139 0.2×	123 0.3×	113 0.4×	185 0.9×	117	1.2k
Hamdi Tolga Kahraman Türkiye	23	881 1.1×	698 1.1×	93 0.2×	76 0.3×	75 0.4×	88	1.9k
Yueting Xu China	13	1.3k 1.6×	203 0.3×	63 0.2×	87 0.3×	131 0.7×	24	2.0k
Abdelhadi Raihani Morocco	26	487 0.6×	338 0.6×	95 0.2×	57 0.2×	59 0.3×	132	1.5k

Countries citing papers authored by Min Shi

Since Specialization

Citations

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

Fields of papers citing papers by Min Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Shi

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

Li, Minghan, Congcong Wen, Yu Tian, et al.. (2025). FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA. IEEE Transactions on Medical Imaging. PP. 1–1.

2.

Shi, Min, et al.. (2025). Deep learning model for differentiating thyroid eye disease and orbital myositis on computed tomography (CT) imaging. Orbit. 44(6). 758–766.

3.

Yang, Xiansheng, et al.. (2024). uLiDR: An inertial-assisted unmodulated visible light positioning system for smartphone-based pedestrian navigation. Information Fusion. 113. 102579–102579. 20 indexed citations

4.

Liu, Yan, James Doulgeris, Min Shi, et al.. (2024). The Frontiers of Smart Healthcare Systems. Healthcare. 12(23). 2330–2330. 1 indexed citations

5.

Zhang, Xiangping, Jianxun Liu, & Min Shi. (2024). GRRLN: Gated Recurrent Residual Learning Networks for code clone detection. Journal of Software Evolution and Process. 36(7).

6.

Yang, Xiansheng, Yuan Zhuang, Fuqiang Gu, et al.. (2023). DeepWiPos: A Deep Learning-Based Wireless Positioning Framework to Address Fingerprint Instability. IEEE Transactions on Vehicular Technology. 72(6). 8018–8034. 29 indexed citations

7.

Shi, Min, Ping Fu, Joseph V. Bonventre, & Kyle W. McCracken. (2023). Directed differentiation of ureteric bud and collecting duct organoids from human pluripotent stem cells. Nature Protocols. 18(8). 2485–2508. 5 indexed citations

8.

Zhang, Xiangping, Jianxun Liu, & Min Shi. (2023). A parallel deep learning-based code clone detection model. Journal of Parallel and Distributed Computing. 181. 104747–104747. 2 indexed citations

9.

Kang, Guosheng, et al.. (2022). Web Services Clustering via Exploring Unified Content and Structural Semantic Representation. IEEE Transactions on Network and Service Management. 19(4). 4082–4096. 18 indexed citations

10.

Shi, Min, Yufei Tang, Xingquan Zhu, et al.. (2022). Feature-Attention Graph Convolutional Networks for Noise Resilient Learning. IEEE Transactions on Cybernetics. 52(8). 7719–7731. 12 indexed citations

11.

Yin, Rui, et al.. (2021). An Evaluation Method for New Energy Power Prediction Based on Flexibility Matrix and TOPSIS Method. Electric Power Construction. 42(2). 35. 2 indexed citations

12.

Zhang, Xiangping, Jianxun Liu, Buqing Cao, & Min Shi. (2021). Web service classification based on information gain theory and bidirectional long short‐term memory with attention mechanism. Concurrency and Computation Practice and Experience. 33(13). 5 indexed citations

13.

Shi, Min, Yuan Zhuang, Yufei Tang, et al.. (2021). Web Service Network Embedding Based on Link Prediction and Convolutional Learning. IEEE Transactions on Services Computing. 15(6). 3620–3633. 14 indexed citations

14.

Shi, Min, Yufei Tang, Xingquan Zhu, & Jianxun Liu. (2020). Multi-Label Graph Convolutional Network Representation Learning. IEEE Transactions on Big Data. 8(5). 1169–1181. 21 indexed citations

15.

Shi, Min, Yufei Tang, & Jianxun Liu. (2018). Functional and Contextual Attention-Based LSTM for Service Recommendation in Mashup Creation. IEEE Transactions on Parallel and Distributed Systems. 30(5). 1077–1090. 64 indexed citations

16.

Shi, Min, et al.. (2017). A Hybrid Approach for Automatic Mashup Tag Recommendation.. Journal of Web Engineering. 16. 676–692. 9 indexed citations

17.

Shi, Min. (2011). Analysis on the Form of Acid Rain in Dalian Based on Air Trajectory Clustering. Environmental Science & Technology. 1 indexed citations

18.

Shi, Min. (2009). Research on Inter-bridge Connected Adaptive Backup Power Automatic Throw-in. Dianli xitong zidonghua. 1 indexed citations

19.

Shi, Min. (2005). Improved Multi-Objective Particle Swarm Algorithm. 4 indexed citations

20.

Shi, Min. (2004). Study on Public Information Display in FIDS. Microcomputer Development.

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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