Tingwen Wang

779 total citations · 1 hit paper
8 papers, 668 citations indexed

About

Tingwen Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Materials Chemistry. According to data from OpenAlex, Tingwen Wang has authored 8 papers receiving a total of 668 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Materials Chemistry. Recurrent topics in Tingwen Wang's work include Medical Image Segmentation Techniques (2 papers), AI in cancer detection (2 papers) and Microplastics and Plastic Pollution (1 paper). Tingwen Wang is often cited by papers focused on Medical Image Segmentation Techniques (2 papers), AI in cancer detection (2 papers) and Microplastics and Plastic Pollution (1 paper). Tingwen Wang collaborates with scholars based in China and United States. Tingwen Wang's co-authors include Chunshan Song, Xinwen Guo, Keyan Li, Sufeng An, Junhu Wang, Guanghui Zhang, Wenna Zhang, Shu Miao, Jeffrey T. Miller and Yuchun Tang and has published in prestigious journals such as ACS Nano, Applied Surface Science and RSC Advances.

In The Last Decade

Tingwen Wang

8 papers receiving 654 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.

High-Density Ultra-small Clusters and Single-Atom Fe Sites Embedded in Graphitic Carbon Nitride (g-C₃N₄) for Highly Efficient Catalytic Advanced Oxidation Processes

2018 533 citations Sufeng An, Guanghui Zhang et al. ACS Nano profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tingwen Wang China	6	465	342	151	134	80	8	668
Soochan Lee South Korea	12	71 0.2×	304 0.9×	80 0.5×	43 0.3×	40 0.5×	35	662
Rui Zhai China	13	164 0.4×	232 0.7×	34 0.2×	194 1.4×	13 0.2×	44	559
Zhengyuan Zhang China	19	1.1k 2.3×	714 2.1×	45 0.3×	548 4.1×	146 1.8×	27	1.6k
Song Tian China	12	106 0.2×	175 0.5×	114 0.8×	71 0.5×	8 0.1×	21	488
Hongbo Wang China	25	991 2.1×	1.0k 3.0×	58 0.4×	466 3.5×	19 0.2×	54	1.5k
Haonan Qin China	16	341 0.7×	260 0.8×	18 0.1×	210 1.6×	13 0.2×	51	704
Ping An China	12	106 0.2×	218 0.6×	40 0.3×	145 1.1×	10 0.1×	23	488

Countries citing papers authored by Tingwen Wang

Since Specialization

Citations

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

Fields of papers citing papers by Tingwen Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tingwen Wang

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

All Works

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8 of 8 papers shown

1.

Hu, Jianfeng, et al.. (2025). Artificial Intelligence-Assisted Clinical Decision-Making: A Perspective on Advancing Personalized Precision Medicine for Elderly Diabetes Patients. Journal of Multidisciplinary Healthcare. Volume 18. 4643–4651. 1 indexed citations

2.

Zhang, Chunyun, et al.. (2021). Deep semantic-aware network for zero-shot visual urban perception. International Journal of Machine Learning and Cybernetics. 13(5). 1197–1211. 5 indexed citations

3.

Wang, Tingwen, Keyan Li, Sufeng An, Chunshan Song, & Xinwen Guo. (2018). Facile and green synthesis of TiN/C as electrode materials for supercapacitors. Applied Surface Science. 470. 241–249. 22 indexed citations

4.

An, Sufeng, Guanghui Zhang, Tingwen Wang, et al.. (2018). High-Density Ultra-small Clusters and Single-Atom Fe Sites Embedded in Graphitic Carbon Nitride (g-C₃N₄) for Highly Efficient Catalytic Advanced Oxidation Processes. ACS Nano. 12(9). 9441–9450. 533 indexed citations breakdown →

5.

Li, Haixia, Xianjing Meng, Tingwen Wang, Yuchun Tang, & Yilong Yin. (2017). Breast masses in mammography classification with local contour features. BioMedical Engineering OnLine. 16(1). 44–44. 46 indexed citations

6.

Wei, Dafu, et al.. (2016). Preparation of nonleaching antimicrobial polypropylene wax and its application in polypropylene. Journal of Applied Polymer Science. 134(4). 18 indexed citations

7.

Xi, Xiaoming, et al.. (2016). Breast tumor segmentation with prior knowledge learning. Neurocomputing. 237. 145–157. 40 indexed citations

8.

Pan, Dong, Le Wang, Tingwen Wang, et al.. (2016). Room-temperature spin transport in InAs nanowire lateral spin valve. RSC Advances. 6(79). 75736–75740. 3 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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