Junhua Ding

1.3k total citations · 1 hit paper
83 papers, 776 citations indexed

About

Junhua Ding is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Junhua Ding has authored 83 papers receiving a total of 776 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 25 papers in Information Systems and 18 papers in Computer Networks and Communications. Recurrent topics in Junhua Ding's work include Software Testing and Debugging Techniques (15 papers), Cell Image Analysis Techniques (12 papers) and Service-Oriented Architecture and Web Services (12 papers). Junhua Ding is often cited by papers focused on Software Testing and Debugging Techniques (15 papers), Cell Image Analysis Techniques (12 papers) and Service-Oriented Architecture and Web Services (12 papers). Junhua Ding collaborates with scholars based in United States, China and Netherlands. Junhua Ding's co-authors include Xin‐Hua Hu, Haihua Chen, Xin‐Hua Hu, Xiaojun Kang, Jiangping Chen, Lei Wu, Wei Lu, Venkat N. Gudivada, Jun Q. Lu and Dianxiang Xu and has published in prestigious journals such as Optics Express, IEEE Access and Pattern Recognition.

In The Last Decade

Junhua Ding

75 papers receiving 751 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.

A comparative study of automated legal text classification using random forests and deep learning

2021 131 citations Haihua Chen, Jiangping Chen et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Junhua Ding United States	15	368	218	158	145	83	83	776
Cornelio Yáñez-Márquéz Mexico	21	567 1.5×	232 1.1×	94 0.6×	78 0.5×	144 1.7×	142	1.2k
Wolfgang Mueller Germany	19	233 0.6×	171 0.8×	193 1.2×	196 1.4×	105 1.3×	132	1.1k
Ahmed Mohammed Alghamdi Saudi Arabia	13	317 0.9×	113 0.5×	38 0.2×	188 1.3×	202 2.4×	77	719
Shih‐Hao Hung Taiwan	13	119 0.3×	197 0.9×	71 0.4×	434 3.0×	97 1.2×	94	773
Troy Raeder United States	11	487 1.3×	137 0.6×	14 0.1×	72 0.5×	132 1.6×	14	972
Deepak Kumar India	12	79 0.2×	224 1.0×	101 0.6×	123 0.8×	91 1.1×	106	584
Alexandr Kuznetsov Ukraine	21	590 1.6×	302 1.4×	32 0.2×	340 2.3×	534 6.4×	198	1.3k
K. Lakshmanan India	13	282 0.8×	82 0.4×	40 0.3×	118 0.8×	114 1.4×	38	555
Rizik Al-Sayyed Jordan	11	296 0.8×	261 1.2×	42 0.3×	211 1.5×	63 0.8×	47	694

Countries citing papers authored by Junhua Ding

Since Specialization

Citations

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

Fields of papers citing papers by Junhua Ding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junhua Ding

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

All Works

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20 of 20 papers shown

1.

Ding, Junhua, Haihua Chen, Yunhe Feng, & K. S. M. Tozammel Hossain. (2024). Applications of Deep Learning Techniques. Electronics. 13(17). 3354–3354. 2 indexed citations

2.

Ding, Junhua, et al.. (2024). Fault Diagnosis of Dry Gas Seal Operation Status Based on Acoustic Emission Monitoring. Lubricants. 12(2). 35–35. 4 indexed citations

3.

Ding, Junhua, Huyen Nguyen, & Haihua Chen. (2024). Evaluation of Question-Answering Based Text Summarization using LLM Invited Paper. 142–149.

4.

Ding, Junhua, Li Zhang, Yingke Zhu, et al.. (2024). Fire Retardancy of Poly(ethylene 2,5-furandicarboxylate-co-ethylene terephthalate) Regulated by Phosphinate. ACS Applied Polymer Materials. 6(11). 6697–6705.

5.

Chen, Haihua, et al.. (2023). Measurement and Identification of Informative Reviews for Automated Summarization. 33. 146–151. 1 indexed citations

6.

Chen, Haihua, et al.. (2023). Construction and evaluation of a domain-specific knowledge graph for knowledge discovery. Information Discovery and Delivery. 51(4). 358–370. 2 indexed citations

7.

Ding, Junhua, et al.. (2023). Bias Analysis in Language Models using An Association Test and Prompt Engineering. 356–363. 1 indexed citations

8.

Chen, Haihua, et al.. (2022). Data Curation and Quality Evaluation for Machine Learning-Based Cyber Intrusion Detection. IEEE Access. 10. 121900–121923. 14 indexed citations

9.

Tang, Mingwei, et al.. (2022). A Quantitative Study of Impact of Incentive to Quality of Software Reviews. 54–63. 1 indexed citations

10.

Wu, Fan, et al.. (2020). A Survey on the Use of Data Clustering for Intrusion Detection System in Cybersecurity. International Journal of Network Security & Its Applications. 12(1). 1–18. 15 indexed citations

11.

Ding, Junhua, et al.. (2018). An Approach for Validating Quality of Datasets for Machine Learning. 2795–2803. 9 indexed citations

12.

Ding, Junhua, Patrícia D. L. Machado, & Marc Roper. (2017). Proceedings of the 12th International Workshop on Automation of Software Testing. International Conference on Software Engineering. 3 indexed citations

13.

Ding, Junhua, Xiaojun Kang, & Xin‐Hua Hu. (2017). Validating a Deep Learning Framework by Metamorphic Testing. 28–34. 42 indexed citations

14.

Ding, Junhua, Wei Song, & Dongmei Zhang. (2014). MODELING AND ANALYSIS OF MOBILE PUSH NOTIFICATION SERVICES USING PETRI NETS. 2(4). 52–64. 1 indexed citations

15.

Ding, Junhua, Dianxiang Xu, & Jidong Ge. (2013). An Approach for Analyzing Software Specifications in Petri Nets.. Software Engineering and Knowledge Engineering. 411–416. 1 indexed citations

16.

Ding, Junhua & Dianxiang Xu. (2012). Model-Based Metamorphic Testing: A Case Study.. Software Engineering and Knowledge Engineering. 363–368. 2 indexed citations

17.

Jacobs, Kenneth M., Li V. Yang, Junhua Ding, et al.. (2009). Diffraction imaging of spheres and melanoma cells with a microscope objective. Journal of Biophotonics. 2(8-9). 521–527. 31 indexed citations

18.

Ding, Junhua, Dianxiang Xu, Yi Deng, Peter Clarke, & Xudong He. (2005). Design an Interoperable Mobile Agent System Based on Predicate Transition Net Models.. Software Engineering and Knowledge Engineering. 560–565. 1 indexed citations

19.

He, Xudong, et al.. (2004). Modeling and analyzing security protocols in SAM: A case study.. 115–121. 2 indexed citations

20.

Ding, Junhua, et al.. (1990). Tunable ultraviolet generation by frequency doubling dye laser in BBO crystal. Journal of Tsinghua University(Science and Technology). 30(6). 15–20.

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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