Xiaoting Zhong

446 total citations · 1 hit paper
10 papers, 311 citations indexed

About

Xiaoting Zhong is a scholar working on Materials Chemistry, Structural Biology and Statistical and Nonlinear Physics. According to data from OpenAlex, Xiaoting Zhong has authored 10 papers receiving a total of 311 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Materials Chemistry, 3 papers in Structural Biology and 2 papers in Statistical and Nonlinear Physics. Recurrent topics in Xiaoting Zhong's work include Machine Learning in Materials Science (4 papers), Microstructure and mechanical properties (3 papers) and Advanced Electron Microscopy Techniques and Applications (3 papers). Xiaoting Zhong is often cited by papers focused on Machine Learning in Materials Science (4 papers), Microstructure and mechanical properties (3 papers) and Advanced Electron Microscopy Techniques and Applications (3 papers). Xiaoting Zhong collaborates with scholars based in United States, China and Australia. Xiaoting Zhong's co-authors include T. Yong-Jin Han, Brian Gallagher, Bhavya Kailkhura, Shusen Liu, Anna M. Hiszpanski, Gregory S. Rohrer, Hossein Beladi, David J. Rowenhorst, Herbert M. Miller and Shen J. Dillon and has published in prestigious journals such as Acta Materialia, Journal of the American Ceramic Society and Neural Computing and Applications.

In The Last Decade

Xiaoting Zhong

8 papers receiving 299 citations

Hit Papers

Explainable machine learning in materials science 2022 2026 2023 2024 2022 50 100 150 200
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. Explainable machine learning in materials science
    2022 214 citations Xiaoting Zhong, Brian Gallagher et al. npj Computational Materials profile →

Peers

Xiaoting Zhong
Dongbo Dai China
Fang Ren United States
Qidong Liu China
A. Mukhopadhyay India
Jiang Guo China
He Zhao United States
Ruho Kondo Japan
Nima H. Siboni Germany
Dongbo Dai China
Xiaoting Zhong
Citations per year, relative to Xiaoting Zhong Xiaoting Zhong (= 1×) peers Dongbo Dai

Countries citing papers authored by Xiaoting Zhong

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoting Zhong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoting Zhong

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoting Zhong. A scholar is included among the top collaborators of Xiaoting Zhong 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 Xiaoting Zhong. Xiaoting Zhong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
2.
Zhong, Xiaoting, Brian Gallagher, Shusen Liu, et al.. (2022). Explainable machine learning in materials science. npj Computational Materials. 8(1). 214 indexed citations breakdown →
3.
Liu, Shusen, Bhavya Kailkhura, Jize Zhang, et al.. (2022). Attribution-Driven Explanation of the Deep Neural Network Model via Conditional Microstructure Image Synthesis. ACS Omega. 7(3). 2624–2637. 4 indexed citations
4.
Zhong, Xiaoting, et al.. (2022). Machine Learning Enabled Reproducible Data Analysis for Electron Microscopy. Microscopy and Microanalysis. 28(S1). 3138–3140. 1 indexed citations
5.
Zhong, Xiaoting, et al.. (2021). A study of real-world micrograph data quality and machine learning model robustness. npj Computational Materials. 7(1). 14 indexed citations
6.
7.
Zhong, Xiaoting, et al.. (2019). Grain boundary curvatures in polycrystalline SrTiO 3 : Dependence on grain size, topology, and crystallography. Journal of the American Ceramic Society. 102(11). 7003–7014. 13 indexed citations
8.
Zhan, Choujun, et al.. (2018). A model for collective behaviour propagation: a case study of video game industry. Neural Computing and Applications. 32(9). 4507–4517. 8 indexed citations
9.
Shen, Yufeng, Xiaoting Zhong, He Liu, et al.. (2018). Determining grain boundary energies from triple junction geometries without discretizing the five-parameter space. Acta Materialia. 166. 126–134. 11 indexed citations
10.
Zhong, Xiaoting, David J. Rowenhorst, Hossein Beladi, & Gregory S. Rohrer. (2016). The five-parameter grain boundary curvature distribution in an austenitic and ferritic steel. Acta Materialia. 123. 136–145. 46 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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2026