Kai Zhou

2.7k total citations
153 papers, 1.5k citations indexed

About

Kai Zhou is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Electrical and Electronic Engineering. According to data from OpenAlex, Kai Zhou has authored 153 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Nuclear and High Energy Physics, 20 papers in Astronomy and Astrophysics and 18 papers in Electrical and Electronic Engineering. Recurrent topics in Kai Zhou's work include High-Energy Particle Collisions Research (53 papers), Particle physics theoretical and experimental studies (33 papers) and Quantum Chromodynamics and Particle Interactions (33 papers). Kai Zhou is often cited by papers focused on High-Energy Particle Collisions Research (53 papers), Particle physics theoretical and experimental studies (33 papers) and Quantum Chromodynamics and Particle Interactions (33 papers). Kai Zhou collaborates with scholars based in China, Germany and United States. Kai Zhou's co-authors include Pengfei Zhuang, Long-Gang Pang, Lingxiao Wang, H. Stöcker, Zhe Xu, Shuzhe Shi, Horst Stoecker, Nu Xu, Jiaxing Zhao and Y. G. and has published in prestigious journals such as Physical Review Letters, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Kai Zhou

130 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kai Zhou China	21	845	221	137	133	132	153	1.5k
Horst Stoecker Germany	22	1.6k 1.9×	436 2.0×	311 2.3×	69 0.5×	117 0.9×	124	1.9k
J. J. Toscano Mexico	19	1.1k 1.3×	280 1.3×	165 1.2×	37 0.3×	56 0.4×	97	1.7k
B. C. Barish United States	21	1.1k 1.4×	287 1.3×	322 2.4×	56 0.4×	99 0.8×	75	1.7k
C. Hansen United States	16	352 0.4×	533 2.4×	63 0.5×	55 0.4×	104 0.8×	72	1.1k
M. Gilmore United States	16	353 0.4×	202 0.9×	71 0.5×	24 0.2×	86 0.7×	71	1.0k
M. J. White Australia	20	896 1.1×	552 2.5×	87 0.6×	81 0.6×	49 0.4×	103	1.4k
R. N. Cahn United States	30	2.2k 2.6×	488 2.2×	329 2.4×	59 0.4×	47 0.4×	112	2.9k
R. DeSalvo United States	21	192 0.2×	344 1.6×	344 2.5×	65 0.5×	47 0.4×	86	1.1k
M. Gelfusa Italy	19	520 0.6×	118 0.5×	53 0.4×	248 1.9×	273 2.1×	163	1.4k

Countries citing papers authored by Kai Zhou

Since Specialization

Citations

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

Fields of papers citing papers by Kai Zhou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Zhou

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

Yuan, Hui, et al.. (2025). Hybrid multi-head physics-informed neural network for depth estimation in terahertz imaging. Computer Physics Communications. 312. 109586–109586.

Habibi, Daryoush, et al.. (2025). Diffusion models learn distributions generated by complex Langevin dynamics. 39–39.

Aarts, Gert, et al.. (2025). On learning higher-order cumulants in diffusion models. Machine Learning Science and Technology. 6(2). 25004–25004. 1 indexed citations

Aarts, Gert, Kenji Fukushima, Tetsuo Hatsuda, et al.. (2025). Physics-driven learning for inverse problems in quantum chromodynamics. Nature Reviews Physics. 7(3). 154–163. 15 indexed citations

Zhou, Kai, et al.. (2025). Toward a foundation model for heavy-ion collision experiments based on point-cloud diffusion. Physical review. C. 112(5). 1 indexed citations

Stoecker, Horst, et al.. (2024). Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks. Journal of the Franklin Institute. 361(6). 106671–106671. 14 indexed citations

Gou, Shuiping, et al.. (2024). Hierarchical Knowledge Guided Fault Intensity Diagnosis of Complex Industrial Systems. ArXiv.org. 5657–5668.

Gou, Shuiping, et al.. (2024). Hierarchical cavitation intensity recognition using Sub-Master Transition Network-based acoustic signals in pipeline systems. Expert Systems with Applications. 258. 125155–125155.

Zhou, Kai, et al.. (2023). Polyaniline nanosheets templated from aniline‒acid precipitates and their electrochemical performance for flexible supercapacitor. Electrochimica Acta. 469. 143263–143263. 4 indexed citations

10.

Wang, Lingxiao, et al.. (2023). A neural network reconstruction of the neutron star equation of state via automatic differentiation. 55–55. 1 indexed citations

11.

Wang, Lingxiao, Shuzhe Shi, & Kai Zhou. (2023). Unsupervised learning spectral functions with neural networks. Journal of Physics Conference Series. 2586(1). 12158–12158. 1 indexed citations

12.

Zhou, Kai. (2023). Exploration of extreme QCD matter with deep learning. Journal of Physics Conference Series. 2586(1). 12159–12159.

13.

He, W., Y. G., Long-Gang Pang, Huichao Song, & Kai Zhou. (2023). High-energy nuclear physics meets machine learning. Nuclear Science and Techniques. 34(6). 62 indexed citations

14.

Zhou, Kai, Lingxiao Wang, Long-Gang Pang, & Shuzhe Shi. (2023). Exploring QCD matter in extreme conditions with Machine Learning. Progress in Particle and Nuclear Physics. 135. 104084–104084. 50 indexed citations

15.

Wang, Lingxiao, Lijia Jiang, & Kai Zhou. (2022). Learning Langevin dynamics with QCD phase transition. SHILAP Revista de lepidopterología. 1 indexed citations

16.

Li, Wei, et al.. (2022). CREIME—A Convolutional Recurrent Model for Earthquake Identification and Magnitude Estimation. Journal of Geophysical Research Solid Earth. 127(7). 19 indexed citations

17.

Greif, Moritz, et al.. (2016). Dynamical photon production and v 2 γ in the quark-gluon plasma. Nuclear and Particle Physics Proceedings. 276-278. 345–348. 1 indexed citations

18.

Stoecker, Horst, Kai Zhou, Stefan Schramm, et al.. (2016). Glueballs amass at the RHIC and LHC! the early quarkless first-order phase transition at T = 270 MeV - From pure Yang-Mills glue plasma to Hagedorn glueball states. Repository of the Academy's Library (Library of the Hungarian Academy of Sciences). 10 indexed citations

19.

Zhou, Kai. (2010). Topic Oriented Sentimental Feature Selection Method for News Comments. Zhongwen xinxi xuebao. 3 indexed citations

20.

Zhou, Kai. (2006). Expression and polyclonal antibody preparation of molt-inhibiting hormone 1(MIH1) from the mitten crab Eriocheir japonica sinensis. Dongwu xuebao. 2 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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