Heng Peng

3.1k total citations · 1 hit paper
59 papers, 2.0k citations indexed

About

Heng Peng is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Heng Peng has authored 59 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Statistics and Probability, 17 papers in Artificial Intelligence and 7 papers in Management Science and Operations Research. Recurrent topics in Heng Peng's work include Statistical Methods and Inference (35 papers), Statistical Methods and Bayesian Inference (16 papers) and Advanced Statistical Methods and Models (16 papers). Heng Peng is often cited by papers focused on Statistical Methods and Inference (35 papers), Statistical Methods and Bayesian Inference (16 papers) and Advanced Statistical Methods and Models (16 papers). Heng Peng collaborates with scholars based in China, Hong Kong and United States. Heng Peng's co-authors include Jianqing Fan, Gaorong Li, Lixing Zhu, Tao Huang, Jun Zhang, Li Zhu, Miao Bai-qi, Ying Lü, Yacine Aı̈t-Sahalia and Kun Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

Heng Peng

54 papers receiving 1.9k citations

Hit Papers

Nonconcave penalized likelihood with a diverging number o... 2004 2026 2011 2018 2004 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heng Peng China 18 1.3k 478 201 169 162 59 2.0k
Chenlei Leng Singapore 22 1.4k 1.0× 498 1.0× 194 1.0× 168 1.0× 129 0.8× 75 2.1k
Yanyuan Ma United States 23 1.4k 1.1× 397 0.8× 106 0.5× 104 0.6× 170 1.0× 137 1.9k
Heng Lian China 24 1.3k 1.0× 578 1.2× 112 0.6× 250 1.5× 125 0.8× 222 1.9k
Xuming He United States 31 1.5k 1.2× 378 0.8× 309 1.5× 137 0.8× 144 0.9× 107 2.8k
Young K. Truong United States 22 980 0.7× 307 0.6× 112 0.6× 191 1.1× 169 1.0× 52 1.9k
Lan Wang United States 19 1.0k 0.8× 337 0.7× 155 0.8× 86 0.5× 70 0.4× 60 1.5k
Sadanori Konishi Japan 20 898 0.7× 469 1.0× 139 0.7× 171 1.0× 96 0.6× 88 1.9k
Lixing Zhu China 27 2.5k 1.9× 627 1.3× 77 0.4× 227 1.3× 205 1.3× 190 3.0k
Jianhua Z. Huang United States 18 607 0.5× 378 0.8× 247 1.2× 108 0.6× 45 0.3× 39 1.4k
Pascal Sarda France 15 1.2k 0.9× 489 1.0× 59 0.3× 295 1.7× 150 0.9× 27 1.7k

Countries citing papers authored by Heng Peng

Since Specialization
Citations

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

Fields of papers citing papers by Heng Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heng Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Heng Peng. A scholar is included among the top collaborators of Heng Peng 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 Heng Peng. Heng Peng 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
2.
Dai, Yunqian, et al.. (2025). Microneedle Arrays for Near-Infrared-Controlled Insulin Delivery Based on Thermosensitive Microgel. ACS Applied Materials & Interfaces. 17(23). 33483–33497. 3 indexed citations
3.
Peng, Heng, et al.. (2025). Component selection and variable selection for mixture regression models. Computational Statistics & Data Analysis. 206. 108124–108124.
4.
Peng, Heng, et al.. (2024). Text-Centric Multimodal Contrastive Learning for Sentiment Analysis. Electronics. 13(6). 1149–1149. 1 indexed citations
5.
Peng, Heng, et al.. (2023). Bacterial Diversity Analysis of Chaozhou Sauerkraut Based on High-Throughput Sequencing of Different Production Methods. Fermentation. 9(3). 282–282. 5 indexed citations
6.
Peng, Heng, et al.. (2022). A latent class Cox model for heterogeneous time-to-event data. Journal of Econometrics. 239(2). 105351–105351. 1 indexed citations
7.
Zhang, Song, et al.. (2022). Apathy following Bilateral Deep Brain Stimulation of Subthalamic Nucleus and Globus Pallidus Internus in Parkinson’s Disease: A Meta‐Analysis. Parkinson s Disease. 2022(1). 4204564–4204564. 6 indexed citations
8.
Fang, Kai‐Tai, et al.. (2021). A new type of robust designs for chemometrics and computer experiments. Chemometrics and Intelligent Laboratory Systems. 221. 104474–104474. 4 indexed citations
9.
Cheng, Qing, Yi Yang, Xingjie Shi, et al.. (2020). MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy. NAR Genomics and Bioinformatics. 2(2). lqaa028–lqaa028. 33 indexed citations
10.
Zhang, Feipeng, Heng Peng, & Yong Zhou. (2016). Composite partial likelihood estimation for length-biased and right-censored data with competing risks. Journal of Multivariate Analysis. 149. 160–176. 3 indexed citations
11.
Tong, Tiejun & Heng Peng. (2014). Tail Probability Ratios of Normal and Student’s t Distributions. Communication in Statistics- Theory and Methods. 43(18). 3797–3811. 1 indexed citations
12.
Yang, Yiping, Gaorong Li, & Heng Peng. (2014). Empirical likelihood of varying coefficient errors-in-variables models with longitudinal data. Journal of Multivariate Analysis. 127. 1–18. 21 indexed citations
13.
Tang, Yi, Hua He, Ning Cheng, et al.. (2014). PDGF, NT-3 and IGF-2 in Combination Induced Transdifferentiation of Muscle-Derived Stem Cells into Schwann Cell-Like Cells. PLoS ONE. 9(1). e73402–e73402. 16 indexed citations
14.
Peng, Heng, et al.. (2013). The connection between cross-validation and Akaike information criterion in a semiparametric family. Journal of nonparametric statistics. 25(2). 475–485. 2 indexed citations
15.
Lin, Huazhen & Heng Peng. (2012). Smoothed rank correlation of the linear transformation regression model. Computational Statistics & Data Analysis. 57(1). 615–630. 18 indexed citations
16.
Li, Gaorong, Heng Peng, & Lixing Zhu. (2011). NONCONCAVE PENALIZED M-ESTIMATION WITH A DIVERGING NUMBER OF PARAMETERS. Statistica Sinica. 21(1). 391–419. 74 indexed citations
17.
Zhang, Wenyang & Heng Peng. (2010). Simultaneous confidence band and hypothesis test in generalised varying-coefficient models. Journal of Multivariate Analysis. 101(7). 1656–1680. 31 indexed citations
18.
Li, Gaorong, Sanying Feng, & Heng Peng. (2010). A profile-type smoothed score function for a varying coefficient partially linear model. Journal of Multivariate Analysis. 102(2). 372–385. 16 indexed citations
19.
Cheng, Chung Wah, et al.. (2009). Cancer patients' attitudes towards Chinese medicine: a Hong Kong survey. Chinese Medicine. 4(1). 25–25. 39 indexed citations
20.
Aı̈t-Sahalia, Yacine, Jianqing Fan, & Heng Peng. (2005). Nonparametric Transition-Based Tests for Jump-Diffusions. SSRN Electronic Journal. 9 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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