个人简介
王洪，男，博士，副教授，博士生导师。国家认证高级程序员、系统分析师(2004年获湖南省人事厅高级专业技术资格)。2000年毕业于中南大学英语专业，获文学学士学位；2008毕业于湖南大学计算机应用技术专业，获工学硕士学位；2015年毕业于中南大学统计学专业，获理学博士学位；2017年-2018年，加州大学洛杉矶分校（UCLA）生物统计专业公派博士后。主要从事机器学习和生物统计等方面的研究工作。在Statistics in Medicine、Artificial Intelligence in Medicine 、Knowledge-Based Systems、Reliability Engineering and System Safety等统计和机器学习期刊发表SCI论文20余篇，获软件著作权1项。主持和参加国家社科基金、国家自科基金项目4项，主持省部级目3项，主持企业合作横向课题多项。 是20余种SCI杂志的审稿人。
代表性论文(近5年，#表示共同作者，*表示通讯作者)：
Xuewei Cheng, Sizheng Wang, Hong Wang* and Shu Kay Ng, Deep survival forests for extremely high censored data, Applied Intelligence, 2022, https://doi.org/10.1007/s10489-022-03846-0 (SCI, JCR2区, IF=5.086)
Hong Wang#,Badamasi Abba#, Jianxin Pan*, Classical and Bayesian Estimations of Improved Weibull-Weibull Distribution for Complete and Censored Failure Times Data, Applied Stochastic Models in Business and Industry, 2022, https://doi.org/10.1002/asmb.2698 (SCI，JCR3区，IF=1.338）
Badamasi Abba, Hong Wang*, Hassan S. Bakouch, A Reliability and Survival Model for One and Two Failure Modes System with Applications to Complete and Censored Datasets，Reliability Engineering and System Safety，2022, 223: 108460（SCI，JCR1区，IF=6.188）
Zhou, Lifeng, Wang, Hong*. A Combined Feature Screening Approach of Random Forest and Filter-based Methods for Ultra-high Dimensional Data, Current Bioinformatics, 2022, http://dx.doi.org/10.2174/1574893617666220221120618, (SCI, JCR1区，IF=3.543)
Zhuan Zhang#, Zhenyuan Shen#, Hong Wang*, Shu Kay Ng. A Fast Adaptive Lasso for the Cox Regression via Safe Screening Rules, Journal of Statistical Computation and Simulation, 2021, 91(14): 3005-3027 (SCI, JCR3区，IF=1.424)
Hong Wang, Ning Li, Shanpeng Li, and Gang Li*, JMcmprsk: An R Package for Joint Modelling of Longitudinal and Survival Data with Competing Risks, R Journal, 2021, 13(1): 53-68 (SCI, JCR1区，IF=3.984)
NF Zhao, QX Xu, ML Tang and H Wang*,"Variable screening for near infrared (NIR) spectroscopy data based on ridge partial least squares regression", Combinatorial Chemistry & High Throughput Screening, 2020, 23(8):740-756. (SCI, JCR3区, IF=1.195)
NF Zhao, QX Xu, ML Tang, BY Jiang, ZQ Chen, and H Wang*,"High Dimensional Variable Screening under Multicollinearity",Stat, 2020, 9, e272. (SCI, JCR3区, IF=0.766)
Wang, Hong, and Gang Li*."Extreme Learning Machine Cox Model for High Dimensional Survival Analysis", Statistics in Medicine, 38.12, (2019): 2139-2156, (SCI, JCR1区, IF=1.932)
Wang, Hong, and Lifeng Zhou*. "SurvELM: an R package for high dimensional survival analysis with extreme learning machine", Knowledge-Based Systems, 160 (2018):28-33. （SCI,JCR1区, IF=4.396)
Wang, Hong, Jianxin Wang*, and Lifeng Zhou. "A survival ensemble of extreme learning machine." Applied Intelligence 48.7 (2018): 1846-1858.（SCI,JCR2区, IF=1.983)
Zhou, Lifeng, Hong Wang*, and Qingsong Xu. "Survival forest with partial least squares for high dimensional censored data." Chemometrics and Intelligent Laboratory Systems 175 (2018), 12-21.（SCI,JCR1区, IF=2.701)
Wang, Hong, Xiaolin Chen, and Gang Li*. "Survival Forests with R-Squared Splitting Rules." Journal of Computational Biology 25.4 (2018): 388-395.（SCI,JCR2区, IF=1.191)
Chen, Xiaolin, Xiaojing Chen, and Hong Wang. "Robust feature screening for ultra-high dimensional right censored data via distance correlation." Computational Statistics & Data Analysis 119 (2018): 118-138.（SCI,JCR2区, IF=1.81)
Wang, Hong, and Lifeng Zhou*. "Random survival forest with space extensions for censored data." Artificial Intelligence in Medicine 79 (2017): 52-61.（SCI,JCR1区, IF=2.879)