Qi Ju

1.8k total citations · 1 hit paper
25 papers, 979 citations indexed

About

Qi Ju is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Oceanography. According to data from OpenAlex, Qi Ju has authored 25 papers receiving a total of 979 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Oceanography. Recurrent topics in Qi Ju's work include Natural Language Processing Techniques (10 papers), Topic Modeling (9 papers) and Marine and coastal ecosystems (4 papers). Qi Ju is often cited by papers focused on Natural Language Processing Techniques (10 papers), Topic Modeling (9 papers) and Marine and coastal ecosystems (4 papers). Qi Ju collaborates with scholars based in China, Hong Kong and Sweden. Qi Ju's co-authors include Zhe Zhao, Weijie Liu, Peng Zhou, Zhiruo Wang, Ping Wang, Shen Huang, Bojie Hu, Ruijia Wang, Xiao Wang and Chuan Shi and has published in prestigious journals such as The Science of The Total Environment, Water Research and International Journal of Pharmaceutics.

In The Last Decade

Qi Ju

21 papers receiving 962 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.

K-BERT: Enabling Language Representation with Knowledge Graph

2020 437 citations Weijie Liu, Peng Zhou et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qi Ju China	11	775	240	92	80	44	25	979
Suju Rajan United States	10	399 0.5×	279 1.2×	210 2.3×	45 0.6×	48 1.1×	21	747
Xiaozhi Wang China	10	941 1.2×	195 0.8×	127 1.4×	71 0.9×	83 1.9×	31	1.2k
Ricardo Cerri Brazil	16	494 0.6×	148 0.6×	120 1.3×	225 2.8×	20 0.5×	69	844
Dequan Zheng China	13	415 0.5×	105 0.4×	123 1.3×	57 0.7×	40 0.9×	77	656
Weilin Zhao China	2	481 0.6×	113 0.5×	91 1.0×	43 0.5×	27 0.6×	4	717
Gregor Leban Slovenia	9	159 0.2×	66 0.3×	71 0.8×	134 1.7×	16 0.4×	20	437
Yongfeng Zhang China	11	590 0.8×	200 0.8×	574 6.2×	39 0.5×	84 1.9×	26	875
Marcílio C. P. de Souto Brazil	15	521 0.7×	130 0.5×	86 0.9×	149 1.9×	19 0.4×	56	718
Henry R. Ehrenberg United States	5	499 0.6×	98 0.4×	107 1.2×	68 0.8×	74 1.7×	7	670
Jer Hayes Ireland	6	304 0.4×	37 0.2×	83 0.9×	125 1.6×	16 0.4×	13	453

Countries citing papers authored by Qi Ju

Since Specialization

Citations

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

Fields of papers citing papers by Qi Ju

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qi Ju

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

Ju, Qi, et al.. (2025). Architecting Path Selection Method for Incremental Evolution in System-of-Systems. IEEE Systems Journal. 19(2). 636–647.

2.

Qi, Yuping, et al.. (2023). Promotion of the resistance of human oral epithelial cells to herpes simplex virus type I infection via N6-methyladenosine modification. BMC Oral Health. 23(1). 121–121. 9 indexed citations

3.

Liu, Weijie, Yuejian Fang, Zhe Zhao, et al.. (2022). Multi-stage Distillation Framework for Cross-Lingual Semantic Similarity Matching. 2171–2181.

4.

Cui, Xinyue, Liqun Yang, Qin Hu, et al.. (2021). Co-assembled nanocomplexes of peptide neoantigen Adpgk and Toll-like receptor 9 agonist CpG ODN for efficient colorectal cancer immunotherapy. International Journal of Pharmaceutics. 608. 121091–121091. 27 indexed citations

5.

Bai, Leilei, Qi Ju, Chunliu Wang, et al.. (2021). Responses of steroid estrogen biodegradation to cyanobacterial organic matter biodegradability in the water column of a eutrophic lake. The Science of The Total Environment. 805. 150058–150058. 15 indexed citations

6.

Liu, Weijie, Xin Zhao, Zhe Zhao, et al.. (2021). An Empirical Study on Adaptive Inference for Pretrained Language Model. IEEE Transactions on Neural Networks and Learning Systems. 34(8). 4321–4331. 4 indexed citations

7.

Chen, Xu, Bojie Hu, Yanyang Li, et al.. (2021). Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders. 2619–2630. 49 indexed citations

8.

Ju, Qi, et al.. (2021). [Response of Microbial Community to Natural Organic Matter Input in Lake Sediments].. PubMed. 42(7). 3263–3271. 5 indexed citations

9.

Wang, Ruijia, et al.. (2021). Graph Structure Estimation Neural Networks. 342–353. 87 indexed citations

10.

Chen, Xu, Bojie Hu, Yufan Jiang, et al.. (2020). Dynamic Curriculum Learning for Low-Resource Neural Machine Translation. 3977–3989. 14 indexed citations

11.

Bai, Leilei, Qi Zhang, Qi Ju, et al.. (2020). Priming effect of autochthonous organic matter on enhanced degradation of 17α-ethynylestradiol in water-sediment system of one eutrophic lake. Water Research. 184. 116153–116153. 36 indexed citations

12.

Liu, Weijie, et al.. (2020). FastBERT: a Self-distilling BERT with Adaptive Inference Time. 6035–6044. 173 indexed citations

13.

Ju, Qi, et al.. (2020). Heterogeneous adsorption of macrophyte- and algae-derived dissolved organic matter on goethite in freshwater lakes. Journal of Lake Sciences. 32(4). 1041–1049. 2 indexed citations

14.

Liu, Mengyuan, et al.. (2020). RefineDetLite: A Lightweight One-stage Object Detection Framework for CPU-only Devices. arXiv (Cornell University). 2997–3007. 16 indexed citations

15.

Zhao, Zhe, Hui Chen, Jinbin Zhang, et al.. (2019). UER: An Open-Source Toolkit for Pre-training Models. 241–246. 54 indexed citations

16.

Wang, Hongzhen, et al.. (2019). Text Siamese Network for Video Textual Keyframe Detection. 442–447. 3 indexed citations

17.

Ju, Qi. (2015). An Improved Harris Corner Detection Algorithm. 5 indexed citations

18.

Ju, Qi. (2014). Multi-peak MPP distribution of photovoltaic array. Dianli zidonghua shebei.

19.

Moschitti, Alessandro, Qi Ju, & Richard Johansson. (2012). Modeling Topic Dependencies in Hierarchical Text Categorization. Institutional Research Information System (Università degli Studi di Trento). 759–767. 3 indexed citations

20.

Giunchiglia, Fausto, et al.. (2009). Lightweight Parsing of Natural Language Metadata. Unitn Eprints Research (Università Degli Studi di Trento). 2 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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