Xin Qin

2.4k total citations · 1 hit paper
40 papers, 1.6k citations indexed

About

Xin Qin is a scholar working on Mechanical Engineering, Aerospace Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xin Qin has authored 40 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Mechanical Engineering, 16 papers in Aerospace Engineering and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xin Qin's work include High Temperature Alloys and Creep (20 papers), High-Temperature Coating Behaviors (13 papers) and Context-Aware Activity Recognition Systems (7 papers). Xin Qin is often cited by papers focused on High Temperature Alloys and Creep (20 papers), High-Temperature Coating Behaviors (13 papers) and Context-Aware Activity Recognition Systems (7 papers). Xin Qin collaborates with scholars based in China, United States and Russia. Xin Qin's co-authors include Jindong Wang, Yiqiang Chen, Chaohui Yu, Wen Gao, Chao Yuan, Jie Hou, Guo Jianting, Lu Wang, Lan Zhou and Chunlin Chen and has published in prestigious journals such as Materials Science and Engineering A, Journal of Materials Science and Journal of Alloys and Compounds.

In The Last Decade

Xin Qin

35 papers receiving 1.6k citations

Hit Papers

FedHealth: A Federated Tr... 2020 2026 2022 2024 2020 200 400 600
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.

  1. FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare
    2020 629 citations Yiqiang Chen, Xin Qin et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xin Qin China 19 686 637 258 240 208 40 1.6k
Jongho Shin South Korea 19 120 0.2× 364 0.6× 272 1.1× 88 0.4× 304 1.5× 112 1.5k
Zhipeng Wang China 18 275 0.4× 208 0.3× 112 0.4× 437 1.8× 117 0.6× 123 1.3k
Zuoyin Tang United Kingdom 18 312 0.5× 344 0.5× 153 0.6× 57 0.2× 266 1.3× 61 1.7k
Tao You China 16 153 0.2× 253 0.4× 266 1.0× 55 0.2× 323 1.6× 68 1.1k
Abhishek Kumar India 18 242 0.4× 167 0.3× 44 0.2× 71 0.3× 148 0.7× 98 1.2k
Dawei Sun China 11 150 0.2× 248 0.4× 78 0.3× 68 0.3× 63 0.3× 55 897
Yan Song China 21 426 0.6× 254 0.4× 178 0.7× 139 0.6× 851 4.1× 87 1.6k
Zhan Zhang China 16 102 0.1× 304 0.5× 143 0.6× 51 0.2× 152 0.7× 89 814

Countries citing papers authored by Xin Qin

Since Specialization
Citations

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

Fields of papers citing papers by Xin Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xin Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Xin Qin. A scholar is included among the top collaborators of Xin 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 Xin Qin. Xin 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.
Ji, Shengwei, Eloiza May Galon, Lijun Jia, et al.. (2025). Efficacy and mechanism of action of cipargamin as an antibabesial drug candidate. eLife. 13.
2.
Gu, Yang, et al.. (2025). DDIR: Domain-Disentangled Invariant Representation learning for tailored predictions. Knowledge-Based Systems. 319. 113422–113422.
3.
Yang, Yong, Xin Cao, Tingting Yao, et al.. (2025). Unraveling the relationship between the multilayer network structure and mechanical properties of alkali-free aluminosilicate glass. Journal of Materiomics. 12(1). 101096–101096.
4.
Yang, Meifang, et al.. (2025). The relationship between perceived academic stress and college students’ employment anxiety: the mediating role of psychological resilience. Frontiers in Psychiatry. 16. 1602808–1602808. 3 indexed citations
5.
Guan, Xianjun, et al.. (2024). Tailoring microstructural stability and stress rupture properties of a solid-solution strengthened Fe-Ni-based superalloy via niobium addition. Journal of Alloys and Compounds. 1008. 176628–176628. 3 indexed citations
6.
Wen, Shi-Jie, Yiqiang Chen, Shuai Guo, et al.. (2023). Time Series Adaptation Network for Sensor-Based Cross Domain Human Activity Recognition. 1–8.
7.
8.
Wang, Lu, Jindong Wang, Yiqiang Chen, et al.. (2022). Personalized Federated Learning With Adaptive Batchnorm for Healthcare. IEEE Transactions on Big Data. 10(6). 915–925. 55 indexed citations
9.
Guo, Xiaoling, et al.. (2020). Research on protection system of resonant network in CSNS magnet power supplies. Radiation Detection Technology and Methods. 4(3). 277–283.
10.
Yu, Chaohui, et al.. (2019). DrowsyDet: A Mobile Application for Real-time Driver Drowsiness Detection. 425–432. 7 indexed citations
11.
Qin, Xin, Nikos Aréchiga, Andrew Best, & Jyotirmoy V. Deshmukh. (2019). Automatic Testing and Falsification with Dynamically Constrained Reinforcement Learning. arXiv (Cornell University). 8 indexed citations
12.
Yu, Chaohui, Jindong Wang, Yiqiang Chen, & Xin Qin. (2019). Transfer channel pruning for compressing deep domain adaptation models. International Journal of Machine Learning and Cybernetics. 10(11). 3129–3144. 10 indexed citations
13.
Hu, Xiaobing, Xiangwei Guo, Yujia Wang, et al.. (2017). Microstructural characterization of the η-Ni3(Ti, Al) phase in a long-term-aged Ni-based superalloy. Philosophical Magazine Letters. 97(11). 442–449. 6 indexed citations
14.
Sun, Wenru, et al.. (2013). Effects of Nb/Ti Ratio on the Microstructures of Two Experimental Ni-Based Cast Superalloys. Materials science forum. 747-748. 629–635. 1 indexed citations
15.
Qin, Xin, Guo Jianting, Chao Yuan, et al.. (2012). Long-term thermal exposure responses of the microstructure and properties of a cast Ni-base superalloy. Materials Science and Engineering A. 543. 121–128. 53 indexed citations
16.
Qin, Xin, Guo Jianting, C. Z. Yuan, et al.. (2009). µ-Phase behavior in a cast Ni-base superalloy. Journal of Materials Science. 44(18). 4840–4847. 54 indexed citations
17.
Hou, Jie, Guo Jianting, Gongxian Yang, et al.. (2008). The microstructural instability of a hot corrosion resistant superalloy during long-term exposure. Materials Science and Engineering A. 498(1-2). 349–358. 31 indexed citations
18.
Qin, Xin, Jianting Guo, Chao Yuan, Jie Hou, & H.Q. Ye. (2007). Precipitation and thermal instability of M23C6 carbide in cast Ni-base superalloy K452. Materials Letters. 62(2). 258–261. 44 indexed citations
19.
Qin, Xin, Jianting Guo, Chao Yuan, Jie Hou, & H.Q. Ye. (2007). Thermal stability of primary carbides and carbonitrides in two cast Ni-base superalloys. Materials Letters. 62(15). 2275–2278. 30 indexed citations
20.
Qin, Xin, et al.. (2007). Effects of Long-Term Thermal Exposure on the Microstructure and Properties of a Cast Ni-Base Superalloy. Metallurgical and Materials Transactions A. 38(12). 3014–3022. 90 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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