Xun Huan

1.9k total citations · 1 hit paper
69 papers, 1.1k citations indexed

About

Xun Huan is a scholar working on Statistics, Probability and Uncertainty, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Xun Huan has authored 69 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Statistics, Probability and Uncertainty, 12 papers in Artificial Intelligence and 12 papers in Aerospace Engineering. Recurrent topics in Xun Huan's work include Probabilistic and Robust Engineering Design (19 papers), Model Reduction and Neural Networks (11 papers) and Aerodynamics and Acoustics in Jet Flows (8 papers). Xun Huan is often cited by papers focused on Probabilistic and Robust Engineering Design (19 papers), Model Reduction and Neural Networks (11 papers) and Aerodynamics and Acoustics in Jet Flows (8 papers). Xun Huan collaborates with scholars based in United States, Germany and Italy. Xun Huan's co-authors include Youssef Marzouk, Brendan Kochunas, Krishna Garikipati, Chao Hu, Cosmin Safta, Habib N. Najm, Guilhem Lacaze, Joseph Oefelein, Roger Ghanem and Olga Fink and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Xun Huan

63 papers receiving 1.0k citations

Hit Papers

Uncertainty quantification in machine learning for engine... 2023 2026 2024 2025 2023 25 50 75 100
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. Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
    2023 103 citations Xun Huan et al. profile →

Peers

Xun Huan
John A. Cafeo United States
Koji Shimoyama Japan
Rohit Tripathy United States
John T. Hwang United States
Guillaume Perrin France
Alberto Bernardini Italy
János D. Pintér Canada
Xiaoqun Wang China
Hongzhe Dai China
John A. Cafeo United States
Xun Huan
Citations per year, relative to Xun Huan Xun Huan (= 1×) peers John A. Cafeo

Countries citing papers authored by Xun Huan

Since Specialization
Citations

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

Fields of papers citing papers by Xun Huan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xun Huan

This figure shows the co-authorship network connecting the top 25 collaborators of Xun Huan. A scholar is included among the top collaborators of Xun Huan 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 Xun Huan. Xun Huan 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.
Huan, Xun, et al.. (2025). Bayesian model selection for network discrimination and risk‐informed decision‐making in material flow analysis. Journal of Industrial Ecology. 29(4). 1060–1076.
2.
Huan, Xun, et al.. (2025). A Multifidelity Estimator of the Expected Information Gain for Bayesian Optimal Experimental Design. SIAM/ASA Journal on Uncertainty Quantification. 13(4). 1990–2021.
3.
4.
Sachdeva, Nishtha, Zhenguang Huang, B. van der Holst, et al.. (2025). Decent Estimate of CME Arrival Time From a Data‐Assimilated Ensemble in the Alfvén Wave Solar Atmosphere Model (DECADE‐AWSoM). Space Weather. 23(1). 2 indexed citations
5.
Huan, Xun, et al.. (2025). Mechanical information enhanced battery state-of-health estimation. eTransportation. 25. 100440–100440.
6.
Huan, Xun, et al.. (2025). Variational sequential optimal experimental design using reinforcement learning. Computer Methods in Applied Mechanics and Engineering. 444. 118068–118068. 1 indexed citations
7.
Huan, Xun, et al.. (2025). Bayesian Optimal Experimental Design for Intelligent Data Collection in Material Flow Analysis. Procedia CIRP. 135. 175–180. 1 indexed citations
8.
Duraisamy, Karthik, et al.. (2024). Variational Bayesian optimal experimental design with normalizing flows. Computer Methods in Applied Mechanics and Engineering. 433. 117457–117457. 4 indexed citations
9.
10.
Ho, Kenneth K. Y., Chengyang Huang, Krishna Garikipati, et al.. (2024). Integrating inverse reinforcement learning into data-driven mechanistic computational models: a novel paradigm to decode cancer cell heterogeneity. SHILAP Revista de lepidopterología. 4. 1333760–1333760. 1 indexed citations
11.
Huan, Xun, et al.. (2023). Expert elicitation and data noise learning for material flow analysis using Bayesian inference. Journal of Industrial Ecology. 27(4). 1105–1122. 7 indexed citations
12.
Huan, Xun, et al.. (2023). Bayesian sequential optimal experimental design for nonlinear models using policy gradient reinforcement learning. Computer Methods in Applied Mechanics and Engineering. 416. 116304–116304. 18 indexed citations
13.
Huan, Xun, et al.. (2023). Stochastic deep Koopman model for quality propagation analysis in multistage manufacturing systems. Journal of Manufacturing Systems. 71. 609–619. 2 indexed citations
14.
Cohen, Joseph, Xun Huan, & Jun Ni. (2023). Fault Prognosis of Turbofan Engines. International Journal of Prognostics and Health Management. 14(2). 3 indexed citations
15.
Sachdeva, Nishtha, Zhenguang Huang, Yang Chen, et al.. (2023). Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model. Space Weather. 21(1). 14 indexed citations
16.
Cohen, Joseph, Eunshin Byon, & Xun Huan. (2023). To Trust or Not: Towards Efficient Uncertainty Quantification for Stochastic Shapley Explanations. 4(1). 6 indexed citations
17.
Prabhudesai, Snehal, Nicholas Wang, Xun Huan, et al.. (2021). Stratification by Tumor Grade Groups in a Holistic Evaluation of Machine Learning for Brain Tumor Segmentation. Frontiers in Neuroscience. 15. 740353–740353. 9 indexed citations
18.
Huan, Xun, Cosmin Safta, Khachik Sargsyan, et al.. (2019). Compressive sensing adaptation for polynomial chaos expansions. Journal of Computational Physics. 380. 29–47. 47 indexed citations
19.
Ghanem, Roger, Christian Soize, Cosmin Safta, et al.. (2019). Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds. Journal of Computational Physics. 399. 108930–108930. 22 indexed citations
20.
Huan, Xun, et al.. (2015). Transcriptome Analysis of Cadmium Exposed Jatropha curcas. Zhongguo shengwu gongcheng zazhi. 36(4). 69–77. 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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