Yu Su

6.9k total citations · 2 hit papers
152 papers, 3.7k citations indexed

About

Yu Su is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Yu Su has authored 152 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Artificial Intelligence, 35 papers in Computer Vision and Pattern Recognition and 22 papers in Information Systems. Recurrent topics in Yu Su's work include Topic Modeling (36 papers), Natural Language Processing Techniques (24 papers) and Intelligent Tutoring Systems and Adaptive Learning (18 papers). Yu Su is often cited by papers focused on Topic Modeling (36 papers), Natural Language Processing Techniques (24 papers) and Intelligent Tutoring Systems and Adaptive Learning (18 papers). Yu Su collaborates with scholars based in China, United States and Australia. Yu Su's co-authors include Frédéric Jurie, Enhong Chen, Zhenya Huang, Bingpeng Ma, Qi Liu, Пэйдэ Лю, Yu Yin, Xifeng Yan, Shiguang Shan and Xilin Chen and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and Expert Systems with Applications.

In The Last Decade

Yu Su

144 papers receiving 3.6k citations

Hit Papers

EKT: Exercise-Aware Knowledge Tracing for Student Perform... 2019 2026 2021 2023 2019 2023 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yu Su China 33 2.1k 1.1k 734 533 330 152 3.7k
Vincent W. Zheng Singapore 31 2.7k 1.3× 1.1k 1.0× 315 0.4× 1.3k 2.4× 189 0.6× 79 5.1k
Olfa Nasraoui United States 27 1.6k 0.7× 737 0.7× 209 0.3× 1.2k 2.2× 162 0.5× 164 2.9k
Hisashi Kashima Japan 29 1.7k 0.8× 459 0.4× 336 0.5× 248 0.5× 148 0.4× 136 2.7k
Shimon Whiteson Netherlands 27 2.3k 1.1× 466 0.4× 171 0.2× 346 0.6× 423 1.3× 136 3.5k
Alberto Cano United States 30 1.7k 0.8× 357 0.3× 362 0.5× 448 0.8× 96 0.3× 93 2.6k
Ralf Herbrich United Kingdom 28 2.1k 1.0× 1.0k 0.9× 80 0.1× 791 1.5× 411 1.2× 70 3.6k
Liusheng Huang China 38 2.4k 1.1× 742 0.7× 687 0.9× 931 1.7× 270 0.8× 410 5.9k
Αλέξανδρος Νανόπουλος Germany 26 1.3k 0.6× 711 0.7× 156 0.2× 1.2k 2.3× 240 0.7× 101 2.9k
David Cohn United States 14 3.0k 1.4× 711 0.7× 81 0.1× 522 1.0× 278 0.8× 25 4.0k
Geoffrey J. Gordon United States 34 2.5k 1.2× 1.1k 1.1× 79 0.1× 868 1.6× 539 1.6× 112 4.6k

Countries citing papers authored by Yu Su

Since Specialization
Citations

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

Fields of papers citing papers by Yu Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Su

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Su. A scholar is included among the top collaborators of Yu Su 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 Su. Yu Su is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lei, Zihao, et al.. (2025). Anomaly detection of machinery under time-varying operating conditions based on state-space and neural network modeling. Advanced Engineering Informatics. 65. 103285–103285.
3.
Zhang, Zhifen, Rui Qin, Shaohui Li, et al.. (2025). Surface hardness prediction for laser shock peening using narrow-band MCP-PMT and deep feature fusion with key elements and key frames. Journal of Manufacturing Processes. 136. 228–245. 2 indexed citations
4.
Su, Yu, Yao Wang, Yuan Kong, et al.. (2025). Extended Dissipaton Theory with Application to Adatom–Graphene Composite. Journal of Chemical Theory and Computation. 21(8). 4107–4120. 1 indexed citations
5.
Lei, Zihao, Yu Su, Ke Feng, & Guangrui Wen. (2024). Interpretable operational condition attention-informed domain adaptation network for remaining useful life prediction under variable operational conditions. Control Engineering Practice. 153. 106080–106080. 10 indexed citations
6.
Li, Zhiwen, Zhifen Zhang, Shuai Zhang, et al.. (2024). In-situ monitoring in laser powder bed fusion based on acoustic signal time-frequency synchrosqueezing transform and multi-scale spatially interactive fusion convolutional neural network. Journal of Manufacturing Processes. 126. 471–486. 14 indexed citations
7.
Su, Yu, Yao Wang, Rui–Xue Xu, & YiJing Yan. (2024). Generalized system–bath entanglement theorem for Gaussian environments. The Journal of Chemical Physics. 160(8). 3 indexed citations
8.
Su, Yu, et al.. (2024). Spin relaxation dynamics with a continuous spin environment: The dissipaton equation of motion approach. The Journal of Chemical Physics. 161(14). 5 indexed citations
9.
Su, Yu, et al.. (2024). Extended system–bath entanglement theorem with multiple baths in the presence of external fields. The Journal of Chemical Physics. 161(12). 1 indexed citations
10.
Zhou, Haoxuan, et al.. (2023). A novel denoising strategy based on sparse modeling for rotating machinery fault detection under time-varying operating conditions. Measurement. 210. 112534–112534. 14 indexed citations
11.
Chou, Yi‐Hong, et al.. (2023). Breast Tumor Classification using Short-ResNet with Pixel-based Tumor Probability Map in Ultrasound Images. Ultrasonic Imaging. 45(2). 74–84. 1 indexed citations
12.
Qiao, Li, Zhuoran Li, Hua Wang, et al.. (2023). Sensing User’s Activity, Channel, and Location With Near-Field Extra-Large-Scale MIMO. IEEE Transactions on Communications. 72(2). 890–906. 11 indexed citations
13.
Zhou, Haoxuan, Zihao Lei, Enrico Zio, et al.. (2023). Conditional feature disentanglement learning for anomaly detection in machines operating under time-varying conditions. Mechanical Systems and Signal Processing. 191. 110139–110139. 27 indexed citations
14.
Su, Yu, Zi‐Hao Chen, Yao Wang, et al.. (2023). Extended dissipaton equation of motion for electronic open quantum systems: Application to the Kondo impurity model. The Journal of Chemical Physics. 159(2). 6 indexed citations
15.
Liu, Qi, Enhong Chen, Zhenya Huang, et al.. (2022). NeuralCD: A General Framework for Cognitive Diagnosis. IEEE Transactions on Knowledge and Data Engineering. 35(8). 8312–8327. 57 indexed citations
16.
Su, Yu, et al.. (2022). Electron Transfer under the Floquet Modulation in Donor–Bridge–Acceptor Systems. The Journal of Physical Chemistry A. 126(27). 4554–4561. 6 indexed citations
17.
Chen, Zi‐Hao, et al.. (2022). Coherent excitation energy transfer in model photosynthetic reaction center: Effects of non-Markovian quantum environment. The Journal of Chemical Physics. 157(8). 84119–84119. 9 indexed citations
18.
Su, Yu, Huan Sun, Brian M. Sadler, et al.. (2016). On Generating Characteristic-rich Question Sets for QA Evaluation. 562–572. 54 indexed citations
19.
Wu, Runze, Qi Liu, Yuping Liu, et al.. (2015). Cognitive modelling for predicting examinee performance. International Conference on Artificial Intelligence. 1017–1024. 43 indexed citations
20.
Su, Yu. (2015). Big Data Management Framework based on Virtualization and Bitmap Data Summarization. OhioLink ETD Center (Ohio Library and Information Network).

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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