Xufeng Niu

2.2k total citations
59 papers, 1.8k citations indexed

About

Xufeng Niu is a scholar working on Artificial Intelligence, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Xufeng Niu has authored 59 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 18 papers in Global and Planetary Change and 16 papers in Atmospheric Science. Recurrent topics in Xufeng Niu's work include Quantum Computing Algorithms and Architecture (10 papers), Climate variability and models (8 papers) and Atmospheric and Environmental Gas Dynamics (7 papers). Xufeng Niu is often cited by papers focused on Quantum Computing Algorithms and Architecture (10 papers), Climate variability and models (8 papers) and Atmospheric and Environmental Gas Dynamics (7 papers). Xufeng Niu collaborates with scholars based in United States, China and United Kingdom. Xufeng Niu's co-authors include James B. Elsner, Thomas H. Jagger, Robert Livingston, Chris Landsea, James J. O’Brien, F. Graham Lewis, George C. Tiao, John Sobanjo, Brian H. Bossak and Adrian Barbu and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

Xufeng Niu

59 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xufeng Niu United States 24 834 729 334 239 166 59 1.8k
Bala Rajaratnam United States 24 1.6k 1.9× 1.3k 1.8× 150 0.4× 158 0.7× 159 1.0× 72 3.0k
Thomas H. Jagger United States 25 1.7k 2.1× 1.8k 2.5× 730 2.2× 265 1.1× 32 0.2× 54 2.5k
Eric Gilleland United States 25 2.2k 2.7× 1.6k 2.1× 184 0.6× 109 0.5× 73 0.4× 70 2.9k
JONQUIL BEVAN 4 1.1k 1.3× 518 0.7× 113 0.3× 222 0.9× 102 0.6× 10 2.1k
Andreas Hense Germany 31 2.6k 3.1× 2.7k 3.7× 528 1.6× 203 0.8× 125 0.8× 118 4.0k
Rosa Filgueira Vicente United Kingdom 5 485 0.6× 478 0.7× 165 0.5× 215 0.9× 140 0.8× 11 2.2k
Paul Pilon Canada 16 3.4k 4.1× 1.3k 1.8× 168 0.5× 490 2.1× 77 0.5× 22 4.5k
Raúl R. Cordero Chile 25 760 0.9× 887 1.2× 83 0.2× 243 1.0× 234 1.4× 114 2.1k
James A. Hansen United States 27 665 0.8× 651 0.9× 106 0.3× 168 0.7× 85 0.5× 67 1.7k
Andy Bell United Kingdom 2 465 0.6× 458 0.6× 158 0.5× 200 0.8× 121 0.7× 2 2.0k

Countries citing papers authored by Xufeng Niu

Since Specialization
Citations

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

Fields of papers citing papers by Xufeng Niu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xufeng Niu

This figure shows the co-authorship network connecting the top 25 collaborators of Xufeng Niu. A scholar is included among the top collaborators of Xufeng Niu 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 Xufeng Niu. Xufeng Niu 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.
Niu, Xufeng & Wenping Ma. (2023). Selective quantum ensemble learning inspired by improved AdaBoost based on local sample information. Complex & Intelligent Systems. 9(5). 5173–5183. 3 indexed citations
2.
Niu, Xufeng & Wenping Ma. (2023). Semi-supervised classifier ensemble model for high-dimensional data. Information Sciences. 643. 119203–119203. 7 indexed citations
3.
Niu, Xufeng & Wenping Ma. (2023). An ensemble learning model based on differentially private decision tree. Complex & Intelligent Systems. 9(5). 5267–5280. 1 indexed citations
4.
Niu, Xufeng & Wenping Ma. (2022). An improved multiple populations quantum genetic algorithm. Laser Physics Letters. 19(9). 95203–95203. 4 indexed citations
5.
Niu, Xufeng, et al.. (2022). Tests and classification methods in adaptive designs with applications. Journal of Applied Statistics. 50(6). 1334–1357. 1 indexed citations
6.
Wang, Xinpeng, Xiao Liu, Peng Bi, et al.. (2020). Electrochemically Enabled Embedded Three-Dimensional Printing of Freestanding Gallium Wire-like Structures. ACS Applied Materials & Interfaces. 12(48). 53966–53972. 37 indexed citations
7.
Niu, Xufeng & Wenping Ma. (2020). Design of a novel quantum neural network. Laser Physics Letters. 17(10). 105208–105208. 7 indexed citations
8.
Sobanjo, John, et al.. (2019). Pavement Crack Rating Using Machine Learning Frameworks: Partitioning, Bootstrap Forest, Boosted Trees, Naïve Bayes, and K -Nearest Neighbors. Journal of Transportation Engineering Part B Pavements. 145(3). 4019031–4019031. 44 indexed citations
9.
Lu, Dan, Ming Ye, Philip D. Meyer, et al.. (2013). Effects of error covariance structure on estimation of model averaging weights and predictive performance. Water Resources Research. 49(9). 6029–6047. 42 indexed citations
10.
Chowdhary, Rajesh, et al.. (2011). Integrated Bio-Entity Network: A System for Biological Knowledge Discovery. PLoS ONE. 6(6). e21474–e21474. 25 indexed citations
11.
He, Jianghua, Daniel McGee, & Xufeng Niu. (2009). Application of the Bayesian dynamic survival model in medicine. Statistics in Medicine. 29(3). 347–360. 6 indexed citations
12.
Pu, Wenji & Xufeng Niu. (2005). Selecting mixed-effects models based on a generalized information criterion. Journal of Multivariate Analysis. 97(3). 733–758. 41 indexed citations
13.
O’Brien, James J., et al.. (1998). Effect of El Niño on U.S. Landfalling Hurricanes, Revisited. Bulletin of the American Meteorological Society. 79(11). 2477–2482. 240 indexed citations
14.
Niu, Xufeng. (1997). Extreme value theory for a class of nonstationary time series with applications. The Annals of Applied Probability. 7(2). 9 indexed citations
15.
Niu, Xufeng. (1996). Nonlinear Additive Models for Environmental Time Series, With Applications to Ground-Level Ozone Data Analysis. Journal of the American Statistical Association. 91(435). 1310–1310. 8 indexed citations
16.
Niu, Xufeng & George C. Tiao. (1995). Modeling Satellite Ozone Data. Journal of the American Statistical Association. 90(431). 969–983. 21 indexed citations
17.
Niu, Xufeng. (1995). Asymptotic Properties of Maximum Likelihood Estimates in a Class of Space-Time Regression Models. Journal of Multivariate Analysis. 55(1). 82–104. 4 indexed citations
18.
Niu, Xufeng, John E. Frederick, Michael L. Stein, & George C. Tiao. (1992). Trends in column ozone based on TOMS data: Dependence on month, latitude, and longitude. Journal of Geophysical Research Atmospheres. 97(D13). 14661–14669. 56 indexed citations
19.
Miller, A. J., R. M. Nagatani, George C. Tiao, et al.. (1992). Comparisons of observed ozone and temperature trends in the lower stratosphere. Geophysical Research Letters. 19(9). 929–932. 43 indexed citations
20.
Frederick, John E., Xufeng Niu, & E. Hilsenrath. (1989). The detection and interpretation of long-term changes in ozone from space. Advances in Space Research. 9(7). 317–321. 2 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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