Yao Xie

3.7k total citations · 1 hit paper
136 papers, 2.3k citations indexed

About

Yao Xie is a scholar working on Artificial Intelligence, Statistics, Probability and Uncertainty and Statistics and Probability. According to data from OpenAlex, Yao Xie has authored 136 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 30 papers in Statistics, Probability and Uncertainty and 27 papers in Statistics and Probability. Recurrent topics in Yao Xie's work include Advanced Statistical Process Monitoring (29 papers), Sparse and Compressive Sensing Techniques (18 papers) and Anomaly Detection Techniques and Applications (16 papers). Yao Xie is often cited by papers focused on Advanced Statistical Process Monitoring (29 papers), Sparse and Compressive Sensing Techniques (18 papers) and Anomaly Detection Techniques and Applications (16 papers). Yao Xie collaborates with scholars based in United States, China and Sweden. Yao Xie's co-authors include Jian Li, Peter Stoica, Petre Stoica, Jian Li, Bin Guo, Liyan Xie, Luzhou Xu, Rebecca Willett, Shixiang Zhu and Jiaji Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and The Science of The Total Environment.

In The Last Decade

Yao Xie

125 papers receiving 2.2k 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.

On Probing Signal Design For MIMO Radar

2007 796 citations Yao Xie et al. profile →

Peers

Yao Xie

AE

EEE

BE

SP

AI

You He China

Ya Xue United States

Xiaoming Huo United States

Erçan E. Kuruoğlu Italy

Hamidreza Amindavar Iran

Jun Zhang China

Mihai Anitescu United States

Shen-Shyang Ho United States

Robert Piché Finland

Wynn C. Stirling United States

You He China

Yao Xie

1.7k ×1.8

AE

288 ×0.6

EEE

404 ×0.9

BE

228 ×0.5

SP

731 ×2.5

AI

Citations per year, relative to Yao Xie Yao Xie (= 1×) peers You He

Countries citing papers authored by Yao Xie

Since Specialization

Citations

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

Fields of papers citing papers by Yao Xie

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yao Xie

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

1.

Banja, John D., et al.. (2025). Mitigating Bias in Machine Learning Models with Ethics-Based Initiatives: The Case of Sepsis. The American Journal of Bioethics. 26(2). 96–109. 2 indexed citations

2.

Wang, Jie, Rui Gao, & Yao Xie. (2024). Non-Convex Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets. 843–848. 1 indexed citations

3.

Wang, Jie, et al.. (2023). A manifold two-sample test study: integral probability metric with neural networks. Information and Inference A Journal of the IMA. 12(3). 1867–1897. 3 indexed citations

4.

Xie, Yao, et al.. (2023). Causal Structural Learning from Time Series: A Convex Optimization Approach. 5. 902–909. 2 indexed citations

5.

Xie, Yao, et al.. (2023). Streaming Low-Rank Matrix Data Assimilation and Change Identification. 12. 920–924.

6.

Xie, Yao, et al.. (2023). Causal Graph Discovery From Self and Mutually Exciting Time Series. IEEE Journal on Selected Areas in Information Theory. 4. 747–761. 1 indexed citations

7.

Wang, Haoyun & Yao Xie. (2023). Sequential change‐point detection: Computation versus statistical performance. Wiley Interdisciplinary Reviews Computational Statistics. 16(1). 6 indexed citations

8.

Xia, Tianjiao, et al.. (2022). Ionic specificity mediates the transport and retention of graphene-based nanomaterials in saturated porous media. The Science of The Total Environment. 854. 158724–158724. 4 indexed citations

9.

Wang, Jie, Rui Gao, & Yao Xie. (2021). Two-sample Test using Projected Wasserstein Distance. arXiv (Cornell University). 3320–3325. 4 indexed citations

10.

Wang, Haoyun, et al.. (2020). Uncertainty Quantification for Inferring Hawkes Networks. Neural Information Processing Systems. 33. 7125–7134. 2 indexed citations

11.

Zhu, Shixiang, et al.. (2020). Distributionally Robust $k$-Nearest Neighbors for Few-Shot Learning. arXiv (Cornell University).

12.

Xia, Tianjiao, Yixuan Lin, Shun‐Li Li, et al.. (2020). Co-transport of negatively charged nanoparticles in saturated porous media: Impacts of hydrophobicity and surface O-functional groups. Journal of Hazardous Materials. 409. 124477–124477. 40 indexed citations

13.

Zhu, Shixiang & Yao Xie. (2019). Crime Linkage Detection by Spatio-Temporal-Textual Point Processes.. arXiv (Cornell University). 2 indexed citations

14.

Zhu, Shixiang, Shuang Li, & Yao Xie. (2019). Interpretable Generative Neural Spatio-Temporal Point Processes. arXiv (Cornell University).

15.

Zhu, Shixiang, Shuang Li, & Yao Xie. (2019). Reinforcement Learning of Spatio-Temporal Point Processes.. arXiv (Cornell University). 2 indexed citations

16.

Xie, Liyan, Yao Xie, & George V. Moustakides. (2019). Asynchronous Multi-Sensor Change-Point Detection for Seismic Tremors. 787–791. 5 indexed citations

17.

Gao, Rui, Liyan Xie, Yao Xie, & Huan Xu. (2018). Robust Hypothesis Testing Using Wasserstein Uncertainty Sets. arXiv (Cornell University). 31. 7902–7912. 4 indexed citations

18.

Liu, Qinghua & Yao Xie. (2017). Fully Distributed Multi-sensor Change-point Detection.. arXiv (Cornell University). 2 indexed citations

19.

Xie, Yao, et al.. (2017). Uncertainty quantification and design for noisy matrix completion - a unified framework. arXiv (Cornell University). 2 indexed citations

20.

Calderbank, Robert, Andrew Thompson, & Yao Xie. (2014). On block coherence of frames. Applied and Computational Harmonic Analysis. 38(1). 50–71. 16 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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