Chenglin Miao

2.5k total citations · 1 hit paper
49 papers, 1.7k citations indexed

About

Chenglin Miao is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chenglin Miao has authored 49 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 14 papers in Electrical and Electronic Engineering and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chenglin Miao's work include Adversarial Robustness in Machine Learning (13 papers), Mobile Crowdsensing and Crowdsourcing (11 papers) and Privacy-Preserving Technologies in Data (11 papers). Chenglin Miao is often cited by papers focused on Adversarial Robustness in Machine Learning (13 papers), Mobile Crowdsensing and Crowdsourcing (11 papers) and Privacy-Preserving Technologies in Data (11 papers). Chenglin Miao collaborates with scholars based in United States, China and Canada. Chenglin Miao's co-authors include Lü Su, Wenjun Jiang, Hongfei Xue, Yaliang Li, Fenglong Ma, Aidong Zhang, Ye Yuan, Shuochao Yao, Wenyao Xu and Mengdi Huai and has published in prestigious journals such as The Science of The Total Environment, Energy Policy and Ecological Indicators.

In The Last Decade

Chenglin Miao

47 papers receiving 1.7k citations

Hit Papers

align trajectories

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.

Towards Environment Independent Device Free Human Activity Recognition

2018 417 citations Wenjun Jiang, Chenglin Miao et al. profile →

Peers

Chenglin Miao

EEE

AI

CSA

CVPR

CNC

Shuochao Yao United States

Yuanqing Zheng Hong Kong

Wei Xi China

Xianping Tao China

Stephan Sigg Finland

Guangtao Xue China

Huajie Shao United States

Chenren Xu China

Fan Ye United States

Hongzi Zhu China

Shuochao Yao United States

Chenglin Miao

650 ×1.0

EEE

540 ×0.8

AI

163 ×0.4

CSA

789 ×2.1

CVPR

529 ×1.9

CNC

Citations per year, relative to Chenglin Miao Chenglin Miao (= 1×) peers Shuochao Yao

Countries citing papers authored by Chenglin Miao

Since Specialization

Citations

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

Fields of papers citing papers by Chenglin Miao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chenglin Miao

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

All Works

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20 of 20 papers shown

1.

Miao, Chenglin, et al.. (2024). Towards Smartphone-based 3D Hand Pose Reconstruction Using Acoustic Signals. ACM Transactions on Sensor Networks. 20(5). 1–32. 1 indexed citations

2.

Tao, Jian, et al.. (2024). Divergent climatic effects on forest greenness modulated by temperature and precipitation gradients in the Yellow River Basin, China. Ecological Indicators. 158. 111553–111553. 1 indexed citations

3.

Liu, Zihao, Tianhao Wang, Mengdi Huai, & Chenglin Miao. (2024). Backdoor Attacks via Machine Unlearning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(13). 14115–14123. 8 indexed citations

4.

Zhu, Yi, et al.. (2024). Malicious Attacks against Multi-Sensor Fusion in Autonomous Driving. 436–451. 9 indexed citations

5.

Miao, Chenglin, Zhengyan Chen, & Aoxiang Zhang. (2024). Green technology innovation and carbon emission efficiency: The moderating role of environmental uncertainty. The Science of The Total Environment. 938. 173551–173551. 41 indexed citations

6.

Zhu, Yi, et al.. (2024). An Online Defense against Object-based LiDAR Attacks in Autonomous Driving. 380–393.

7.

Afshan, Sahar, et al.. (2023). Do economic growth and globalization are drivers of sustainable resources management? New insights from BRICS countries. Resources Policy. 87. 104314–104314. 2 indexed citations

8.

Xue, Hongfei, Qiming Cao, Chenglin Miao, et al.. (2023). Towards Generalized mmWave-based Human Pose Estimation through Signal Augmentation. 1–15. 36 indexed citations

9.

Huang, Jinyang, Bin Liu, Chenglin Miao, et al.. (2023). PhyFinAtt: An Undetectable Attack Framework Against PHY Layer Fingerprint-Based WiFi Authentication. IEEE Transactions on Mobile Computing. 23(7). 7753–7770. 26 indexed citations

10.

Zhu, Yi, Chenglin Miao, Hongfei Xue, et al.. (2023). TileMask: A Passive-Reflection-based Attack against mmWave Radar Object Detection in Autonomous Driving. 1317–1331. 12 indexed citations

11.

Zhu, Yi, et al.. (2022). Demo: Attacking LiDAR Semantic Segmentation in Autonomous Driving. 1 indexed citations

12.

Huai, Mengdi, Tianhang Zheng, Chenglin Miao, Liuyi Yao, & Aidong Zhang. (2022). On the Robustness of Metric Learning: An Adversarial Perspective. ACM Transactions on Knowledge Discovery from Data. 16(5). 1–25. 5 indexed citations

13.

Huang, Jinyang, et al.. (2021). PhaseAnti: An Anti-Interference WiFi-Based Activity Recognition System Using Interference-Independent Phase Component. IEEE Transactions on Mobile Computing. 22(5). 2938–2954. 12 indexed citations

14.

Xu, Xinyi, Lingjuan Lyu, Xingjun Ma, et al.. (2021). Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning. Neural Information Processing Systems. 34. 20 indexed citations

15.

Jin, Haiming, Chenglin Miao, Lü Su, et al.. (2020). Joint Charging and Relocation Recommendation for E-Taxi Drivers via Multi-Agent Mean Field Hierarchical Reinforcement Learning. IEEE Transactions on Mobile Computing. 21(4). 1274–1290. 46 indexed citations

16.

Zhang, Hengtong, Tianhang Zheng, Jing Gao, et al.. (2019). Towards Data Poisoning Attack against Knowledge Graph Embedding.. arXiv (Cornell University). 5 indexed citations

17.

Huai, Mengdi, Hongfei Xue, Chenglin Miao, et al.. (2019). Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm. 2535–2541. 14 indexed citations

18.

Miao, Chenglin, Lü Su, Wenjun Jiang, Yaliang Li, & Miaomiao Tian. (2017). A lightweight privacy-preserving truth discovery framework for mobile crowd sensing systems. 1–9. 89 indexed citations

19.

Jiang, Wenjun, Chenglin Miao, Lü Su, et al.. (2017). Towards Quality Aware Information Integration in Distributed Sensing Systems. IEEE Transactions on Parallel and Distributed Systems. 29(1). 198–211. 10 indexed citations

20.

Miao, Chenglin, et al.. (2010). Competence Set Expansion Decision-making Analysis Based on Important Degree Coefficient. Canadian social science. 3(6). 49–52. 1 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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