Yiming Li

3.3k total citations · 1 hit paper
82 papers, 1.5k citations indexed

About

Yiming Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Yiming Li has authored 82 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 31 papers in Computer Vision and Pattern Recognition and 10 papers in Signal Processing. Recurrent topics in Yiming Li's work include Adversarial Robustness in Machine Learning (18 papers), Anomaly Detection Techniques and Applications (13 papers) and Privacy-Preserving Technologies in Data (7 papers). Yiming Li is often cited by papers focused on Adversarial Robustness in Machine Learning (18 papers), Anomaly Detection Techniques and Applications (13 papers) and Privacy-Preserving Technologies in Data (7 papers). Yiming Li collaborates with scholars based in China, United States and Singapore. Yiming Li's co-authors include Shu‐Tao Xia, Yong Jiang, Zhifeng Li, Jinghuan Guo, Yaqing Liu, Keyu Chen, Xuefeng Jiang, Yubo Zhou, Jia Li and Deqing Hu and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Yiming Li

71 papers receiving 1.4k citations

Hit Papers

Backdoor Learning: A Survey 2022 2026 2023 2024 2022 50 100 150 200 250
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.

  1. Backdoor Learning: A Survey
    2022 280 citations Yiming Li, Yong Jiang et al. IEEE Transactions on Neural Networks and Learning Systems profile →

Peers

Yiming Li
Daqing Chen China
Zhi‐Hua Zhou China
Jia Zhao China
Gang Xie China
M. Srinivas India
Suparna De United Kingdom
Liang Chang China
Lusi Li United States
Junwei Zhou China
Daqing Chen China
Yiming Li
Citations per year, relative to Yiming Li Yiming Li (= 1×) peers Daqing Chen

Countries citing papers authored by Yiming Li

Since Specialization
Citations

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

Fields of papers citing papers by Yiming Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yiming Li

This figure shows the co-authorship network connecting the top 25 collaborators of Yiming Li. A scholar is included among the top collaborators of Yiming Li 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 Yiming Li. Yiming Li 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.
Li, Yiming, Linghui Zhu, Yang Bai, et al.. (2025). MOVE: Effective and Harmless Ownership Verification via Embedded External Features. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(6). 4734–4751. 3 indexed citations
2.
Luo, Wei, et al.. (2025). FLARE: Toward Universal Dataset Purification Against Backdoor Attacks. IEEE Transactions on Information Forensics and Security. 20. 6459–6473. 1 indexed citations
3.
Luo, Bin, et al.. (2025). Type recognition and parameter identification of power quality disturbances using improved 1D-YOLO and multi-task learning. International Journal of Electrical Power & Energy Systems. 168. 110681–110681.
4.
Cui, Yi, et al.. (2025). Accurate prediction of attitude angles in the measurement while drilling system through backpropagation neural networks. Measurement Science and Technology. 36(6). 65101–65101. 1 indexed citations
5.
Yi, Biao, et al.. (2024). BadActs: A Universal Backdoor Defense in the Activation Space. 5339–5352. 2 indexed citations
6.
Qian, Yaguan, Yiming Li, Wei Wang, et al.. (2024). Evading backdoor defenses: Concealing genuine backdoors through scapegoat strategy. Computers & Security. 150. 104225–104225.
7.
Li, Yiming, et al.. (2024). PointNCBW: Toward Dataset Ownership Verification for Point Clouds via Negative Clean-Label Backdoor Watermark. IEEE Transactions on Information Forensics and Security. 20. 191–206. 5 indexed citations
8.
Li, Yiming, et al.. (2024). Backdoor Attack With Sparse and Invisible Trigger. IEEE Transactions on Information Forensics and Security. 19. 6364–6376. 12 indexed citations
9.
Wang, Yingshuo, Xiaoqing Liu, Jing Li, et al.. (2024). Identification of mycoplasma pneumonia in children based on fusion of multi-modal clinical free-text description and structured test data. Health Informatics Journal. 30(2). 1 indexed citations
10.
Zhang, Pengcheng, et al.. (2024). Toward Stealthy Backdoor Attacks Against Speech Recognition via Elements of Sound. IEEE Transactions on Information Forensics and Security. 19. 5852–5866. 12 indexed citations
11.
Song, Chuanbiao, et al.. (2024). Regional Adversarial Training for Better Robust Generalization. International Journal of Computer Vision. 132(10). 4510–4520. 2 indexed citations
12.
Li, Yiming, et al.. (2023). Portfolio Selection via Graph-Aware Gaussian Processes With Generalized Gaussian Likelihood. IEEE Transactions on Artificial Intelligence. 5(2). 505–515. 3 indexed citations
13.
Li, Yiming, et al.. (2023). Black-Box Dataset Ownership Verification via Backdoor Watermarking. IEEE Transactions on Information Forensics and Security. 18. 2318–2332. 43 indexed citations
14.
Gao, Ying-Hua, Yiming Li, Linghui Zhu, et al.. (2023). Not All Samples Are Born Equal: Towards Effective Clean-Label Backdoor Attacks. Pattern Recognition. 139. 109512–109512. 21 indexed citations
15.
Li, Yiming, Yong Jiang, Zhifeng Li, & Shu‐Tao Xia. (2022). Backdoor Learning: A Survey. IEEE Transactions on Neural Networks and Learning Systems. 35(1). 5–22. 280 indexed citations breakdown →
16.
Zhao, Laiping, et al.. (2022). SDCBench: A Benchmark Suite for Workload Colocation and Evaluation in Datacenters. SHILAP Revista de lepidopterología. 2022. 1 indexed citations
17.
Zhu, Linghui, et al.. (2021). A Fine-Grained Differentially Private Federated Learning Against Leakage From Gradients. IEEE Internet of Things Journal. 9(13). 11500–11512. 27 indexed citations
18.
Li, Jiawei, et al.. (2020). TNT: An Interpretable Tree-Network-Tree Learning Framework using Knowledge Distillation. Entropy. 22(11). 1203–1203. 13 indexed citations
19.
Xu, Jia, Yiming Li, Yong Jiang, & Shu‐Tao Xia. (2020). Adversarial Defense Via Local Flatness Regularization. 2196–2200. 12 indexed citations
20.
Li, Yiming & Lifeng Xi. (2018). Manhattan property of geodesic paths on self-affine carpets. Archiv der Mathematik. 111(3). 279–285. 8 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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