Carl Yang

4.0k total citations
130 papers, 1.6k citations indexed

About

Carl Yang is a scholar working on Artificial Intelligence, Molecular Biology and Statistical and Nonlinear Physics. According to data from OpenAlex, Carl Yang has authored 130 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Artificial Intelligence, 23 papers in Molecular Biology and 22 papers in Statistical and Nonlinear Physics. Recurrent topics in Carl Yang's work include Advanced Graph Neural Networks (48 papers), Topic Modeling (39 papers) and Complex Network Analysis Techniques (22 papers). Carl Yang is often cited by papers focused on Advanced Graph Neural Networks (48 papers), Topic Modeling (39 papers) and Complex Network Analysis Techniques (22 papers). Carl Yang collaborates with scholars based in United States, China and Germany. Carl Yang's co-authors include Jiawei Han, Yuxin Xiao, Chao Zhang, Yizhou Sun, Quan Yuan, Yu Zhang, Hejie Cui, Lifang He, Lichao Sun and Philip S. Yu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, NeuroImage and Stroke.

In The Last Decade

Carl Yang

110 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Carl Yang United States	21	1.1k	435	260	240	175	130	1.6k
Palash Goyal United States	8	1.1k 1.0×	329 0.8×	614 2.4×	226 0.9×	251 1.4×	30	1.6k
Sungchul Kim United States	19	943 0.9×	237 0.5×	360 1.4×	304 1.3×	143 0.8×	93	1.4k
Weitong Chen Australia	16	667 0.6×	388 0.9×	91 0.3×	137 0.6×	33 0.2×	53	1.3k
Hongyun Cai Singapore	6	1.1k 1.0×	294 0.7×	620 2.4×	250 1.0×	234 1.3×	7	1.5k
Partha Talukdar United States	31	2.3k 2.1×	346 0.8×	142 0.5×	502 2.1×	231 1.3×	120	3.0k
Jianxin Li China	26	1.8k 1.7×	691 1.6×	311 1.2×	315 1.3×	104 0.6×	132	2.4k
Erheng Zhong Hong Kong	18	587 0.5×	372 0.9×	137 0.5×	293 1.2×	30 0.2×	28	1.1k
Sanjay Kumar India	21	600 0.5×	191 0.4×	423 1.6×	183 0.8×	57 0.3×	100	1.3k
Daixin Wang China	7	1.5k 1.4×	391 0.9×	922 3.5×	374 1.6×	370 2.1×	10	2.0k
Eunyee Koh United States	19	762 0.7×	233 0.5×	363 1.4×	396 1.6×	102 0.6×	76	1.2k

Countries citing papers authored by Carl Yang

Since Specialization

Citations

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

Fields of papers citing papers by Carl Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carl Yang

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

Luo, Linhao, Carl Yang, Evgeny Kharlamov, & Shirui Pan. (2025). Integrating Large Language Models and Knowledge Graphs for Next-level AGI. 33–36.

Yang, Carl, et al.. (2025). Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks. PubMed. 2025. 6118–6128.

Tan, Yanchao, et al.. (2025). Graph-Oriented Instruction Tuning of Large Language Models for Generic Graph Mining. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(1). 155–169. 2 indexed citations

Yang, Carl, et al.. (2025). Boosting E-commerce Content Diversity: A Graph-based RAG Approach with User Reviews. 3495–3506.

Fu, Zening, et al.. (2024). A simple but tough-to-beat baseline for fMRI time-series classification. NeuroImage. 303. 120909–120909. 1 indexed citations

Yang, Carl, Zhuangdi Zhu, Zheng Xu, et al.. (2024). FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics. 6718–6719.

Tan, Yanchao, Wenzhong Guo, Weiming Liu, et al.. (2024). Logical Relation Modeling and Mining in Hyperbolic Space for Recommendation. 1310–1323.

Cui, Hejie, Yue Yu, Xuan Kan, et al.. (2024). Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models. PubMed. 2024. 15496–15523. 5 indexed citations

Ho, Joyce C., et al.. (2024). PromptLink: Leveraging Large Language Models for Cross-Source Biomedical Concept Linking. PubMed. 2024. 2589–2593. 4 indexed citations

10.

Ma, Wenjing, et al.. (2024). Uncertainty-Aware Pre-Trained Foundation Models for Patient Risk Prediction via Gaussian Process. PubMed. 2024(Companion). 1162–1165. 1 indexed citations

11.

Shi, Wenqi, Yuchen Zhuang, Yue Yu, et al.. (2024). EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records. PubMed. 2024. 22315–22339. 21 indexed citations

12.

Zheng, Da, Jun Ma, Vassilis N. Ioannidis, et al.. (2023). Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications. PubMed. 2023. 5270–5281. 13 indexed citations

13.

Cui, Hejie, et al.. (2023). Transformer-Based Hierarchical Clustering for Brain Network Analysis. 1–5. 5 indexed citations

14.

Shen, Jiaming, et al.. (2023). HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting. PubMed. 2023. 2052–2056. 7 indexed citations

15.

Tan, Yanchao, Weiming Liu, Fan Wang, et al.. (2023). Contrastive Intra- and Inter-Modality Generation for Enhancing Incomplete Multimedia Recommendation. 6234–6242. 9 indexed citations

16.

Dai, Wei, Hejie Cui, Xuan Kan, Ying Guo, & Carl Yang. (2022). Transformer-Based Hierarchical Clustering for Brain Network Analysis (Extended Abstract). 2022 IEEE International Conference on Big Data (Big Data). 4970–4971. 1 indexed citations

17.

Yang, Yi, Hejie Cui, & Carl Yang. (2022). Pre-train Graph Neural Networks for Brain Network Analysis (Extended Abstract). 2022 IEEE International Conference on Big Data (Big Data). 4993–4994. 4 indexed citations

18.

Xiao, Yuxin, Zecheng Zhang, Yuning Mao, Carl Yang, & Jiawei Han. (2022). SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2395–2409. 20 indexed citations

19.

Yang, Carl, Yuxin Xiao, Yu Zhang, Yizhou Sun, & Jiawei Han. (2020). Heterogeneous Network Representation Learning: Survey, Benchmark, Evaluation, and Beyond. arXiv (Cornell University). 24 indexed citations

20.

Liu, Zhihong, et al.. (2011). Modelling growth of five different colour types of mink. South African Journal of Animal Science. 41(2). 14 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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