Jia Chen

1.8k total citations · 1 hit paper
96 papers, 1.1k citations indexed

About

Jia Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Jia Chen has authored 96 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 32 papers in Computer Vision and Pattern Recognition and 23 papers in Information Systems. Recurrent topics in Jia Chen's work include Topic Modeling (14 papers), Information Retrieval and Search Behavior (8 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Jia Chen is often cited by papers focused on Topic Modeling (14 papers), Information Retrieval and Search Behavior (8 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Jia Chen collaborates with scholars based in China, United States and Singapore. Jia Chen's co-authors include Yue Zhang, Qin Jin, Shizhe Chen, Alexander G. Hauptmann, Xiaobo Liang, Jianxin Li, Ming Zhong, Yiqun Liu, Jiaxin Mao and Shaoping Ma and has published in prestigious journals such as Nano Letters, Chemistry of Materials and Small.

In The Last Decade

Jia Chen

79 papers receiving 1.1k 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.

Dynamic network embedding survey

2021 154 citations Jia 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
Jia Chen China	17	564	353	196	93	76	96	1.1k
Shikun Feng China	13	670 1.2×	392 1.1×	118 0.6×	59 0.6×	70 0.9×	37	1.2k
Sheng Gao China	17	648 1.1×	225 0.6×	230 1.2×	60 0.6×	113 1.5×	91	1.0k
Yingyu Liang United States	17	1.1k 2.0×	354 1.0×	144 0.7×	74 0.8×	145 1.9×	56	1.6k
Yuexin Wu China	14	797 1.4×	262 0.7×	225 1.1×	71 0.8×	44 0.6×	59	1.2k
Shotaro Akaho Japan	15	510 0.9×	204 0.6×	156 0.8×	32 0.3×	135 1.8×	100	981
Jiezhong Qiu China	12	714 1.3×	185 0.5×	179 0.9×	113 1.2×	38 0.5×	22	1.2k
Giuseppe Sansonetti Italy	17	288 0.5×	184 0.5×	356 1.8×	76 0.8×	113 1.5×	49	737
Hao Huang China	14	376 0.7×	120 0.3×	85 0.4×	117 1.3×	102 1.3×	89	665
Bert Huang United States	18	766 1.4×	228 0.6×	176 0.9×	112 1.2×	95 1.3×	50	1.3k

Countries citing papers authored by Jia Chen

Since Specialization

Citations

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

Fields of papers citing papers by Jia Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jia Chen

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

1.

Chen, Jia, Li Sheng, Zonglong Li, et al.. (2025). Enhancing Gas Adsorption in Three-Dimensional Covalent Organic Frameworks via Conformational Effects. Chemistry of Materials. 37(14). 5217–5225.

2.

Cao, Shaosheng, Tong Xu, Zuozhu Liu, et al.. (2025). PaRT: Enhancing Proactive Social Chatbots with Personalized Real-Time Retrieval. 4269–4274.

3.

Zhao, Jing, Yuansheng Gao, Jia Chen, et al.. (2025). Identifying Risk Factors and Constructing Predictive Models for Wearing‐Off and Dyskinesia in Chinese Patients With Parkinson's Disease on Long‐Term Levodopa Therapy. CNS Neuroscience & Therapeutics. 31(8). e70544–e70544. 1 indexed citations

4.

Lin, Qiongbin, et al.. (2025). An adaptive hybrid approach for online battery state of charge estimation. Journal of Energy Storage. 115. 116023–116023. 3 indexed citations

5.

Chen, Jia, Y.F. Shen, Miao Wang, & Wen‐Cui Li. (2024). A high-efficiency pre-lithiation strategy for Li-ion capacitor achieved by the synergistic effect of pre-lithiation and solid electrolyte interface film modification. Journal of Energy Storage. 99. 113420–113420. 4 indexed citations

6.

Zhan, Jingtao, Qingyao Ai, Yiqun Liu, Jia Chen, & Shaoping Ma. (2024). Capability-aware Prompt Reformulation Learning for Text-to-Image Generation. 2145–2155. 2 indexed citations

7.

Zhan, Jingtao, et al.. (2024). Scaling Laws For Dense Retrieval. 1339–1349. 5 indexed citations

8.

Chen, Jia, et al.. (2024). Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs. 1–10.

9.

Ma, Chaoyong, et al.. (2024). A novel cross domain diagnosis method based on physical feature weighting and deep residual shrinkage network. Measurement Science and Technology. 36(1). 0161b6–0161b6.

10.

Zheng, Hailong, Hailong Xie, Yongfei Hu, et al.. (2024). RIscoper 2.0: A deep learning tool to extract RNA biomedical relation sentences from literature. Computational and Structural Biotechnology Journal. 23. 1469–1476.

11.

Ai, Qingyao, et al.. (2024). Wikiformer: Pre-training with Structured Information of Wikipedia for Ad-Hoc Retrieval. Proceedings of the AAAI Conference on Artificial Intelligence. 38(17). 19026–19034. 1 indexed citations

12.

Li, Haitao, et al.. (2023). SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval. 1035–1044. 16 indexed citations

13.

Xu, Ziyue, Jia Chen, Xin Chen, et al.. (2023). Improving Tumor Classification by Reusing Self-Predicted Segmentation of Medical Images as Guiding Knowledge. IEEE Journal of Biomedical and Health Informatics. 28(1). 122–133. 4 indexed citations

14.

Gao, Weitao, Li Sheng, Jia Chen, et al.. (2023). Converting Nafion into Li⁺‐Conductive Nanoporous Materials (Small 37/2023). Small. 19(37). 3 indexed citations

15.

Fan, Yixing, et al.. (2022). Pre-training Methods in Information Retrieval. 16(3). 178–317. 26 indexed citations

16.

Xu, Derek, et al.. (2022). SV-Learn: Learning Matrix Singular Values with Neural Networks. 1 indexed citations

17.

Chen, Jia, et al.. (2020). Entity Enhanced BERT Pre-training for Chinese NER. 6384–6396. 41 indexed citations

18.

Chen, Jia. (2020). An EAP Needs Analysis for Non-English Major Graduate Students. 41(6). 106–119. 1 indexed citations

19.

Chen, Jia, Xiaobo Liang, & Yue Zhang. (2019). Cross-Domain NER using Cross-Domain Language Modeling. 2464–2474. 87 indexed citations

20.

Zhang, Kaicheng, Xiaofeng Wang, Jujia Zhang, et al.. (2019). OPTICAL OBSERVATIONS OF THE TYPE IA SUPERNOVA SN 2011fe IN M101 FOR NEARLY 500 DAYS. OakTrust (Texas A&M University Libraries). 28 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.

Explore authors with similar magnitude of impact