Yu Ding

1.4k total citations
62 papers, 1.0k citations indexed

About

Yu Ding is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Yu Ding has authored 62 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Control and Systems Engineering, 14 papers in Artificial Intelligence and 12 papers in Computer Networks and Communications. Recurrent topics in Yu Ding's work include Fault Detection and Control Systems (13 papers), Machine Fault Diagnosis Techniques (12 papers) and Reliability and Maintenance Optimization (7 papers). Yu Ding is often cited by papers focused on Fault Detection and Control Systems (13 papers), Machine Fault Diagnosis Techniques (12 papers) and Reliability and Maintenance Optimization (7 papers). Yu Ding collaborates with scholars based in China, United States and Australia. Yu Ding's co-authors include Chen Lü, Jian Ma, Liang Ma, Laifa Tao, Chao Wang, Yujie Cheng, Mingliang Suo, Xinwei Wang, Lei Wang and Xiaohua Gao and has published in prestigious journals such as Applied Energy, Expert Systems with Applications and IEEE Access.

In The Last Decade

Yu Ding

58 papers receiving 993 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yu Ding China	19	362	220	202	181	162	62	1.0k
Honghui Dong China	17	345 1.0×	192 0.9×	121 0.6×	72 0.4×	177 1.1×	91	951
Ying Zheng China	22	828 2.3×	246 1.1×	158 0.8×	173 1.0×	311 1.9×	127	1.5k
Liang Tang China	21	286 0.8×	210 1.0×	312 1.5×	179 1.0×	115 0.7×	77	1.3k
Miguel Martínez-García United Kingdom	22	348 1.0×	287 1.3×	207 1.0×	71 0.4×	133 0.8×	55	1.3k
Jilun Tian China	12	531 1.5×	143 0.7×	185 0.9×	128 0.7×	178 1.1×	23	908
Zihao Meng China	9	225 0.6×	325 1.5×	125 0.6×	295 1.6×	186 1.1×	21	925
Shuai Zheng China	12	480 1.3×	95 0.4×	158 0.8×	49 0.3×	195 1.2×	25	960
Pritesh Shah India	19	844 2.3×	417 1.9×	162 0.8×	140 0.8×	318 2.0×	90	1.7k
Yu Zheng China	16	328 0.9×	120 0.5×	86 0.4×	86 0.5×	332 2.0×	69	1.3k
Wu Deng China	22	454 1.3×	131 0.6×	348 1.7×	44 0.2×	248 1.5×	57	1.3k

Countries citing papers authored by Yu Ding

Since Specialization

Citations

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

Fields of papers citing papers by Yu Ding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Ding

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

Zhao, Qin, et al.. (2025). Semi-supervised contrastive fault diagnosis with uncertainty-aware and performance-guided adaptive thresholds under limited labeled and imbalanced data. ISA Transactions. 167(Pt B). 1191–1206.

Ding, Yu, Zhidong Li, Bin Liang, et al.. (2025). Can GNNs Learn Link Heuristics? a Concise Review and Evaluation of Link Prediction Methods. IEEE Transactions on Big Data. 12(1). 1–14.

Ding, Yu, et al.. (2024). Deep-Learning-Assisted Optical Transmitter Fingerprint Identification Based on the Constellation Diagram. IEEE Internet of Things Journal. 11(17). 28635–28648. 2 indexed citations

Yang, Xinyu, Wanzeng Kong, Li Zhu, et al.. (2024). TSFAN: tensorized spatial-frequency attention network with domain adaptation for cross-session EEG-based biometric recognition. Journal of Neural Engineering. 21(4). 46005–46005. 3 indexed citations

Ding, Yu, et al.. (2024). A rail defect detection framework under class-imbalanced conditions based on improved you only look once network. Engineering Applications of Artificial Intelligence. 138. 109351–109351. 2 indexed citations

Kong, Wanzeng, et al.. (2023). Fusion Graph Representation of EEG for Emotion Recognition. Sensors. 23(3). 1404–1404. 26 indexed citations

Ding, Yu, et al.. (2023). Reliability Analysis of Phased-Mission Systems Using Bayesian Networks. 377–387. 1 indexed citations

Zhao, Qin, Yu Ding, Chen Lü, et al.. (2023). An adaptive fault diagnosis framework under class-imbalanced conditions based on contrastive augmented deep reinforcement learning. Expert Systems with Applications. 234. 121001–121001. 22 indexed citations

Gao, Xiaohua, Lei Wang, Xichao Su, et al.. (2023). Conditional probability based multi-objective cooperative task assignment for heterogeneous UAVs. Engineering Applications of Artificial Intelligence. 123. 106404–106404. 46 indexed citations

10.

Gu, Rong, Kai Zhang, Zhihao Xu, et al.. (2022). Fluid: Dataset Abstraction and Elastic Acceleration for Cloud-native Deep Learning Training Jobs. 2022 IEEE 38th International Conference on Data Engineering (ICDE). 2182–2195. 35 indexed citations

11.

Zhao, Yu, et al.. (2020). Video object segmentation based on motion-aware ROI prediction and adaptive reference updating. Expert Systems with Applications. 167. 114153–114153. 6 indexed citations

12.

Ma, Jian, Xue Liu, Xinyu Zou, et al.. (2020). Degradation prognosis for proton exchange membrane fuel cell based on hybrid transfer learning and intercell differences. ISA Transactions. 113. 149–165. 37 indexed citations

13.

Li, Xiaolian, et al.. (2020). Message Queue Optimization Model Based on Periodic Execution and Category Priority. Journal of Physics Conference Series. 1486(2). 22046–22046. 2 indexed citations

14.

Ding, Yu, Miaomiao Chen, Chen Ya, et al.. (2020). HDAC3i‐Finder: A Machine Learning‐based Computational Tool to Screen for HDAC3 Inhibitors. Molecular Informatics. 40(3). e2000105–e2000105. 23 indexed citations

15.

Sun, Jinwen, Chen Lü, & Yu Ding. (2016). Fault diagnosis for hydraulic pump based on intrinsic time-scale decomposition and softmax regression. Vibroengineering PROCEDIA. 10. 229–234. 2 indexed citations

16.

Ding, Yu, Jian Ma, & Ye Tian. (2015). Health assessment and fault classification for hydraulic pump based on LR and softmax regression. Journal of Vibroengineering. 17(4). 1805–1816. 11 indexed citations

17.

Ding, Yu & Satish Bukkapatnam. (2015). Challenges and needs for automating nano image processing for material characterization. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9556. 95560Z–95560Z. 4 indexed citations

18.

Ding, Yu, Jian Ma, & Ye Tian. (2014). Performance assessment and fault classification for hydraulic pump based on LMD and LR. Vibroengineering PROCEDIA. 4. 194–199. 2 indexed citations

19.

Ding, Yu, et al.. (2010). Heap Taichi. National University of Singapore. 327–336. 26 indexed citations

20.

Ding, Yu, et al.. (2004). Ultra-Tight Coupling (UTC) Technique in GPS RAIM. Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004). 1803–1812. 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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