T. Shao

1.6k total citations
10 papers, 60 citations indexed

About

T. Shao is a scholar working on Artificial Intelligence, Nuclear and High Energy Physics and Control and Systems Engineering. According to data from OpenAlex, T. Shao has authored 10 papers receiving a total of 60 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Nuclear and High Energy Physics and 2 papers in Control and Systems Engineering. Recurrent topics in T. Shao's work include Particle physics theoretical and experimental studies (4 papers), High-Energy Particle Collisions Research (4 papers) and Neural Networks and Applications (3 papers). T. Shao is often cited by papers focused on Particle physics theoretical and experimental studies (4 papers), High-Energy Particle Collisions Research (4 papers) and Neural Networks and Applications (3 papers). T. Shao collaborates with scholars based in China, United States and Italy. T. Shao's co-authors include Che Ming Ko, Jinhui Chen, Zi-Wei Lin, Kai-Jia Sun, Xiaohan Yu, Ke Zhang, N. Xu, Kai Cheng, Qi Yin and Jianyu Zhu and has published in prestigious journals such as Physics Letters B, Information Sciences and Environmental Research.

In The Last Decade

T. Shao

8 papers receiving 58 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
T. Shao China	5	34	12	9	8	4	10	60
H. Eberhardt Germany	3	15 0.4×	7 0.6×	7 0.8×	5 0.6×	6 1.5×	7	40
H. Zeng China	5	19 0.6×	4 0.3×	5 0.6×	21 2.6×	5 1.3×	19	55
Zhi-Cheng Tang China	5	18 0.5×	10 0.8×	8 0.9×	14 1.8×	6 1.5×	22	63
M. Blatzheim Germany	4	23 0.7×	4 0.3×	12 1.3×	3 0.4×	4 1.0×	4	33
D. Sengupta Switzerland	4	34 1.0×	13 1.1×	5 0.6×	4 0.5×		4	45
D. Gadariya Italy	3	19 0.6×	11 0.9×	9 1.0×	2 0.3×	1 0.3×	5	28
E. Dreyer Israel	4	28 0.8×	14 1.2×	3 0.3×	3 0.4×		8	38
N. V. Biesuz Italy	6	23 0.7×	4 0.3×	4 0.4×	8 1.0×		20	58
Levente Molnár Ireland	5	27 0.8×	6 0.5×	4 0.4×	4 0.5×	1 0.3×	8	46
P. Lujan United States	5	33 1.0×	6 0.5×	2 0.2×	8 1.0×		11	47

Countries citing papers authored by T. Shao

Since Specialization

Citations

This map shows the geographic impact of T. Shao'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 T. Shao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Shao more than expected).

Fields of papers citing papers by T. Shao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Shao

This figure shows the co-authorship network connecting the top 25 collaborators of T. Shao. A scholar is included among the top collaborators of T. Shao 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 T. Shao. T. Shao 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:

10 of 10 papers shown

1.

Shao, T., et al.. (2025). Interpretable research of fuzzy methods: A literature survey. Information Fusion. 126. 103524–103524.

2.

Esser, A., L. Doria, M. Hoek, et al.. (2024). A novel FPGA-based data acquisition for high-precision asymmetry measurements at low rates in electron scattering. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1072. 170187–170187. 1 indexed citations

3.

Shao, T., et al.. (2024). Adsorption and catalytic reduction of hexavalent chromium based on nanomaterials: A review on metal, metallic oxide, metallic sulfide and carbon-based catalyst. Environmental Research. 266. 120449–120449. 4 indexed citations

4.

Yu, Xiaohan, et al.. (2023). An interpretable image classification model Combining a fuzzy neural network with a variational autoencoder inspired by the human brain. Information Sciences. 661. 119885–119885. 9 indexed citations

5.

Zhang, Ke, et al.. (2023). A Symmetrical Fuzzy Neural Network Regression Method Coordinating Structure and Parameter Identifications for Regression. Symmetry. 15(9). 1711–1711.

6.

Shao, T., Jinhui Chen, Y. G., & N. Xu. (2022). Production of light antinuclei in pp collisions by dynamical coalescence and their fluxes in cosmic rays near earth. Physical review. C. 105(6). 4 indexed citations

7.

Shao, T., et al.. (2021). The hierarchical task network planning method based on Monte Carlo Tree Search. Knowledge-Based Systems. 225. 107067–107067. 12 indexed citations

8.

Shao, T., et al.. (2020). Enhanced production of strange baryons in high-energy nuclear collisions from a multiphase transport model. Physical review. C. 102(1). 14 indexed citations

9.

Shao, T., Jinhui Chen, Che Ming Ko, Kai-Jia Sun, & N. Xu. (2020). Yield ratio of hypertriton to light nuclei in heavy-ion collisions from = 4.9 GeV to 2.76 TeV *. Chinese Physics C. 44(11). 114001–114001. 7 indexed citations

10.

Shao, T., Jinhui Chen, Che Ming Ko, & Kai-Jia Sun. (2019). Probing QCD critical fluctuations from the yield ratio of strange hadrons in relativistic heavy-ion collisions. Physics Letters B. 801. 135177–135177. 9 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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