Han Liu

6.7k total citations · 2 hit papers
88 papers, 2.7k citations indexed

About

Han Liu is a scholar working on Statistics and Probability, Global and Planetary Change and Artificial Intelligence. According to data from OpenAlex, Han Liu has authored 88 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Statistics and Probability, 18 papers in Global and Planetary Change and 15 papers in Artificial Intelligence. Recurrent topics in Han Liu's work include Statistical Methods and Inference (27 papers), Advanced Statistical Methods and Models (14 papers) and Land Use and Ecosystem Services (11 papers). Han Liu is often cited by papers focused on Statistical Methods and Inference (27 papers), Advanced Statistical Methods and Models (14 papers) and Land Use and Ecosystem Services (11 papers). Han Liu collaborates with scholars based in China, United States and Hong Kong. Han Liu's co-authors include John Lafferty, Larry Wasserman, Fang Han, Yang Ning, Peng Gong, Pradeep Ravikumar, Jie Wang, Ming Yuan, Nicholas Clinton and Shunlin Liang and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

Han Liu

82 papers receiving 2.6k 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.

Annual dynamics of global land cover and its long-term changes from 1982 to 2015

2020 265 citations Han Liu et al. profile →
China’s current forest age structure will lead to weakened carbon sinks in the near future

2023 87 citations Han Liu et al. profile →

Peers

Han Liu

SP

GPC

AI

ECOLO

WST

Hans R. Künsch Switzerland

Manuel Febrero–Bande Spain

Hannah J. White United Kingdom

Jürgen Pilz Austria

D. J. Best Australia

Hsin‐Cheng Huang Taiwan

James V. Zidek Canada

Ana Ferreira Portugal

Denis Allard France

Bala Rajaratnam United States

Hans R. Künsch Switzerland

Han Liu

1.2k ×1.3

SP

784 ×1.5

GPC

682 ×1.3

AI

81 ×0.2

ECOLO

259 ×1.2

WST

Citations per year, relative to Han Liu Han Liu (= 1×) peers Hans R. Künsch

Countries citing papers authored by Han Liu

Since Specialization

Citations

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

Fields of papers citing papers by Han Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Han Liu

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

Liu, Han, et al.. (2024). Century‐Long Variations in Surface Incident Solar Radiation Over Japan——Characterized by Observations and Reanalyses. International Journal of Climatology. 44(15). 5358–5370. 2 indexed citations

2.

Liu, Han, et al.. (2024). Mega-constellation satellite maneuver forecast via network with attention mechanism. Advances in Space Research. 75(6). 4942–4962.

3.

Geng, Mengqing, Xuecao Li, Haowei Mu, et al.. (2023). Human footprints in the Global South accelerate biomass carbon loss in ecologically sensitive regions. Global Change Biology. 29(20). 5881–5895. 15 indexed citations

4.

Liao, Xiaobin, Yang Ye, Han Liu, et al.. (2023). Analysis of rainwater storage and use recommendations: From the perspective of DBPs generation and their risks. Journal of Hazardous Materials. 448. 130833–130833. 15 indexed citations

5.

Liu, Han, Wujian Ke, Huiru Chen, Chunmei Liang, & Ligang Yang. (2022). The perceptions of sexuality and sexually transmitted diseases (STDs) among adolescent STD patients: A qualitative study. Journal of Pediatric Nursing. 66. e54–e60.

6.

Liu, Dong, et al.. (2021). Different School Reopening Plans on Coronavirus Disease 2019 Case Growth Rates in the School Setting in the United States. Journal of School Health. 91(5). 370–375. 3 indexed citations

7.

Shi, Yaojiang, Linxiu Zhang, Fang Chang, et al.. (2020). Practices and Experiences of Randomized Controlled Trials in China’s Targeted Poverty Alleviations in Education. 38(8). 1. 1 indexed citations

8.

Yang, Zhuoran, Krishnakumar Balasubramanian, Zhaoran Wang, & Han Liu. (2017). Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma. Neural Information Processing Systems. 30. 6097–6106. 7 indexed citations

9.

Wang, Junfang, et al.. (2017). Evolution of zero-determinant strategy in iterated snowdrift game. Acta Physica Sinica. 66(18). 180203–180203. 5 indexed citations

10.

Zhao, Tianqi, Guang Cheng, & Han Liu. (2016). A partially linear framework for massive heterogeneous data. The Annals of Statistics. 44(4). 1400–1437. 83 indexed citations

11.

Han, Fang & Han Liu. (2016). Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution. Bernoulli. 23(1). 23–57. 22 indexed citations

12.

Long, Meng, Han Liu, Mutai Bao, & Peiyan Sun. (2016). Microbial community structure shifts are associated with temperature, dispersants and nutrients in crude oil-contaminated seawaters. Marine Pollution Bulletin. 111(1-2). 203–212. 44 indexed citations

13.

Ning, Yang & Han Liu. (2014). SPARC: Optimal Estimation and Asymptotic Inference under Semiparametric Sparsity. arXiv (Cornell University). 1 indexed citations

14.

Han, Fang & Han Liu. (2013). Optimal Rates of Convergence of Transelliptical Component Analysis. arXiv (Cornell University). 1 indexed citations

15.

Han, Fang & Han Liu. (2013). Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model. Neural Information Processing Systems. 26. 1941–1949. 2 indexed citations

16.

Han, Fang, Tuo Zhao, & Han Liu. (2013). CODA: high dimensional copula discriminant analysis. Journal of Machine Learning Research. 14(1). 629–671. 34 indexed citations

17.

Liu, Han, Fang Han, & Cun‐Hui Zhang. (2012). Transelliptical Graphical Models. Neural Information Processing Systems. 25. 800–808. 28 indexed citations

18.

Han, Fang & Han Liu. (2012). Semiparametric Principal Component Analysis. Neural Information Processing Systems. 25. 171–179. 10 indexed citations

19.

Liu, Han, John Lafferty, & Larry Wasserman. (2010). Tree Density Estimation. arXiv (Cornell University). 4 indexed citations

20.

Liu, Han & Xi Chen. (2010). Multivariate Dyadic Regression Trees for Sparse Learning Problems. Neural Information Processing Systems. 23. 1441–1449. 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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