Haoxuan Che

668 total citations
9 papers, 148 citations indexed

About

Haoxuan Che is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Haoxuan Che has authored 9 papers receiving a total of 148 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Molecular Biology. Recurrent topics in Haoxuan Che's work include Radiomics and Machine Learning in Medical Imaging (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Topic Modeling (2 papers). Haoxuan Che is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Topic Modeling (2 papers). Haoxuan Che collaborates with scholars based in Hong Kong, China and United States. Haoxuan Che's co-authors include Liantao Wu, Huajie Shao, Tao Wang, Zhibo Wang, Yuwei Wang, Peng Sun, Hao Chen, Haibo Jin, Yi Lin and Yutong Bai and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Journal on Selected Areas in Communications and IEEE Transactions on Medical Imaging.

In The Last Decade

Haoxuan Che

9 papers receiving 147 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Haoxuan Che Hong Kong	4	117	26	24	19	16	9	148
Vasileios Iosifidis Germany	5	134 1.1×	9 0.3×	4 0.2×	16 0.8×	7 0.4×	7	176
Delali Kwasi Dake Ghana	8	53 0.5×	35 1.3×	49 2.0×	25 1.3×	5 0.3×	18	167
Amal Bukhari Saudi Arabia	7	50 0.4×	5 0.2×	30 1.3×	25 1.3×	35 2.2×	23	158
Fatima Haouari Qatar	8	64 0.5×	8 0.3×	46 1.9×	41 2.2×	6 0.4×	14	123
Yuanqin He China	6	218 1.9×	9 0.3×	38 1.6×	29 1.5×	9 0.6×	7	258
Mikhail Yurochkin United States	6	138 1.2×	24 0.9×	13 0.5×	13 0.7×	3 0.2×	19	169
Naomi Saphra United Kingdom	6	74 0.6×	12 0.5×	5 0.2×	39 2.1×	6 0.4×	9	158
Si‐Ahmed Naas Finland	5	219 1.9×	15 0.6×	16 0.7×	26 1.4×	5 0.3×	9	244
Kallista Bonawitz United States	3	60 0.5×	8 0.3×	13 0.5×	14 0.7×	3 0.2×	3	75
David Leroy France	2	152 1.3×	32 1.2×	27 1.1×	16 0.8×	2 0.1×	3	180

Countries citing papers authored by Haoxuan Che

Since Specialization

Citations

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

Fields of papers citing papers by Haoxuan Che

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haoxuan Che

This figure shows the co-authorship network connecting the top 25 collaborators of Haoxuan Che. A scholar is included among the top collaborators of Haoxuan Che 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 Haoxuan Che. Haoxuan Che 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:

9 of 9 papers shown

1.

Che, Haoxuan, Haibo Jin, Zhijie Gu, et al.. (2025). LLM-Driven Medical Report Generation via Communication-Efficient Heterogeneous Federated Learning. IEEE Transactions on Medical Imaging. 45(1). 28–39. 1 indexed citations

2.

Jin, Haibo, et al.. (2025). A Chain of Diagnosis Framework for Accurate and Explainable Radiology Report Generation. IEEE Transactions on Medical Imaging. 44(12). 4986–4997. 1 indexed citations

3.

Che, Haoxuan, et al.. (2025). FedDAG: Federated Domain Adversarial Generation Toward Generalizable Medical Image Analysis. IEEE Transactions on Medical Imaging. 44(12). 4931–4944. 2 indexed citations

4.

Jin, Haibo, Haoxuan Che, Yi Lin, & Hao Chen. (2024). PromptMRG: Diagnosis-Driven Prompts for Medical Report Generation. Proceedings of the AAAI Conference on Artificial Intelligence. 38(3). 2607–2615. 36 indexed citations

5.

Yang, Dawei, et al.. (2024). Unpaired Optical Coherence Tomography Angiography Image Super-Resolution via Frequency-Aware Inverse-Consistency GAN. IEEE Journal of Biomedical and Health Informatics. 29(4). 2695–2705. 2 indexed citations

6.

Che, Haoxuan, et al.. (2024). Rethinking Self-Training for Semi-Supervised Landmark Detection: A Selection-Free Approach. IEEE Transactions on Image Processing. 33. 4952–4965. 2 indexed citations

7.

Che, Haoxuan, et al.. (2023). Image Quality-aware Diagnosis via Meta-knowledge Co-embedding. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 19819–19829. 4 indexed citations

8.

Sun, Peng, Haoxuan Che, Zhibo Wang, et al.. (2021). Pain-FL: Personalized Privacy-Preserving Incentive for Federated Learning. IEEE Journal on Selected Areas in Communications. 39(12). 3805–3820. 85 indexed citations

9.

Zheng, Wei, Yutong Bai, & Haoxuan Che. (2018). A computer‐assisted instructional method based on machine learning in software testing class. Computer Applications in Engineering Education. 26(5). 1150–1158. 15 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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