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李丰
 
发布时间:2014年04月25日    点击次数: 次    更新日期:2023年11月22日

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统计学博士,副教授,硕士研究生导师

办公地址:北京市昌平区沙河高教园中央财经大学(沙河校区)学院1号楼304,邮编102206

个人主页:https://feng.li

室:https://kllab.org

电子邮件feng.li@cufe.edu.cn

李丰,内蒙古鄂尔多斯人,现任中央财经大学统计与数学学院副教授、硕士研究生(统计学、数量经济学和工商管理方向)导师。李丰老师博士毕业于瑞典斯德哥尔摩大学,博士论文曾获瑞典2013年度统计学最佳博士论文奖(CramérPrize),在经济统计、预测方法、大数据分布式学习等方面取得较好的学术积累,主持和参与多项国家级基金项目。李丰老师和他的团队开发自主可控适用于海量数据的开源统计和大数据分析软件。

李丰老师近五年在国际影响力期刊发表30余篇学术论文,其中一篇高被引论文高被引。研究成果发表在统计学期刊JCGS,JBES,经济与预测期EJOR,IJF,JBR,JORS,人工智能与数据挖掘期刊ESWA,SADM和医学期刊BMJ Open,Journal of Surgical Research,Journal of Affective Disorders等。他同时著有Bayesian Modeling of Conditional Densities和《大数据分布式计算与案例》《统计计算》,译著《预测:方法与实践》一书。

研究方向

贝叶斯学习· 计量经济学 · 预测方法 · 大数据分布式学习

*李丰老师热忱欢迎优秀校内本科生(①本校拟录取应用统计学硕专硕和数量经济学硕保研学生②大三以上学有余力同学)加入研究团队。研究团队为优秀本科生提供每周一对一指导、参与KLLAB核心科研项目的机会、与国内外知名大学合作研究的机会。

教育背景

·2008 — 2013 统计学博士,瑞典斯德哥尔摩大学统计学系

博士论文:贝叶斯条件密度建模(获瑞典统计学最佳博士论文,Cramér prize)

·2007 — 2008 统计学硕士,瑞典达拉那大学统计学系

·2003 — 2007 统计学本科,中国人民大学统计学院(获北京市优秀毕业生)

工作经历

·2013年9月至今——先后任中央财经大学统计与数学学院讲师、副教授

·2016年6月至2022年12月——任中央财经大学统计与数学学院副院长、数学教学部副主任

主持课题

·国家社会科学基金一般项目(22BTJ028):全局模型视角下的复杂分层经济预测研究。2022/09-今,项目负责人,在研。

·阿里巴巴创新研究计划:电商场景下的复杂时间序列预测问题研究。2021/09-2023/03、项目负责人。

·国家自然科学基金面上项目(82074282):中医药临床疗效评价中基于目标值法的单臂临床研究方法体系的构建。2021/01-2024/12、主要参与人。

·国家自然科学基金青年项目(11501587):贝叶斯柔性密度方法及其在高维金融数据中的应用。2016/01-2018/12、项目负责人。

·教育部基金项目:贝叶斯弹性高维密度方法在复杂数据的研究。2014/01-2016/12、项目负责人。

【参与课题】

·国家自然科学基金青年项目(11401603):复发事件的均值模型和纵向数据的分位数回归的统计与推断。2015/01-2017/12、参加。

·国家自然科学基金青年项目(71401192):公司财务困境预警模型研究:基于财务波动信息的区间数据刻画方法、2015/01-2017/12、参加。

·国家自然科学基金面上项目(71473279):货币总量转向信用总量:全球虚拟经济与实体经济背离机理与宏观政策应对、2015/01-2017/12、参加。

【代表性成果】

[1].Bohan Zhang, Yanfei Kang, Anastasios Panagiotelis and Feng Li(2023),"Optimal reconciliation with immutable forecasts",European Journal of Operational Research. Vol. 308(1), pp. 650-660.(通讯作者,JCR Q1, IF 6.4, ABS4)

[2].Yanfei Kang, Wei Cao, Fotios Petropoulos and Feng Li(2022),"Forecast with Forecasts: Diversity Matters",European Journal of Operational Research. Vol. 31(1), pp. 180-190.(通讯作者,JCR Q1, IF 6.4, ABS4)

[3].Xuening Zhu,Feng Li and Hansheng Wang (2021),"Least-Square Approximation for a Distributed System",Journal of Computational and Graphical Statistics. Vol. 30(4), pp. 1004-1018.(通讯作者,JCR Q1, IF 3.3)

[4].Xixi Li, Yanfei Kang and Feng Li(2020),"Forecasting with time series imaging",Expert Systems with Applications. Vol. 160, pp. 113680.(通讯作者,JCR Q1, IF 8.5,中科院一区Top)

[5].Feng Li and Yanfei Kang (2018),"Improving forecasting performance using covariate-dependent copula models",International Journal of Forecasting. Vol. 34(3), pp. 456-476.(第一作者,JCR Q1, IF 7.9, ABS3,中科院一区Top)

【学术发表

[34]. Guanyu Zhang,Feng Li, and Yanfei Kang (2023),“Probabilistic Forecast Reconciliation with Kullback-Leibler Divergence Regularization.”The 2023 IEEE International Conference on Data Mining (ICDM): Artificial Intelligence for Time Series Analysis Workhsop (AI4TS) .(通讯作者)

[33]. Yinuo Ren,Feng Li, and Yanfei Kang (2023),“Infinite Forecast Combinations Based on Dirichlet Process.The 2023 IEEE International Conference on Data Mining (ICDM): Artificial Intelligence for Time Series Analysis Workhsop (AI4TS) .(通讯作者)

[32].Feng Li(2023),“A Forecaster’s Review of Judea Pearl’s Causality: Models, Reasoning and Inference, Second Edition, 2009”,International Journal of Forecasting., (In Press)(独立作者)

[31].Li Li,Feng Li and Yanfei Kang (2023),“Forecasting Large Collections of Time Series: Feature-Based Methods”, In Forecasting with Artificial Intelligence: Theory and Applications. Cham , pp. 251-276. Springer Nature Switzerland.

[30].Xiaoqian Wang, Rob J. Hyndman,Feng Li and Yanfei Kang (2023),"Forecast combinations: an over 50-year review",International Journal of Forecasting. Vol. 39(3), pp. 1163-1184.

[29].Li Li, Yanfei Kang, Fotios Petropoulos and Feng Li(2023),"Feature-based intermittent demand forecast combinations: accuracy and inventory implications",International Journal of Production Research.Vol. 61(22), pp. 7557-7572. (通讯作者)

[28].Bohan Zhang, Yanfei Kang, Anastasios Panagiotelis and Feng Li(2023),"Optimal reconciliation with immutable forecasts",European Journal of Operational Research. Vol. 308(1), pp. 650-660.(通讯作者)

[27].Rui Pan, Tunan Ren, Baishan Guo,Feng Li, Guodong Li and Hansheng Wang (2022),"A Note on Distributed Quantile Regression by Pilot Sampling and One-Step Updating",Journal of Business and Economic Statistics. Vol. 40(4), pp. 1691-1700.

[26].Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos and Feng Li(2022),"The uncertainty estimation of feature-based forecast combinations",Journal of the Operational Research Society. Vol. 73(5), pp. 979-993.(通讯作者)

[25].Zhiru Wang, Yu Pang, Mingxin Gan, Martin Skitmore and Feng Li(2022),"Escalator accident mechanism analysis and injury prediction approaches in heavy capacity metro rail transit stations",Safety Science. Vol. 154, pp. 105850.(通讯作者)

[24].Li Li, Yanfei Kang and Feng Li(2022),"Bayesian forecast combination using time-varying features",International Journal of Forecasting. Vol. 39(3), pp. 1287-1302.(通讯作者)

[23].Xiaoqian Wang, Yanfei Kang, Rob J. Hyndman and Feng Li(2022),"Distributed ARIMA models for ultra-long timeseries",International Journal of Forecasting. Vol. 39(3), pp. 1163-1184.(通讯作者)

[22].Matthias Anderer and Feng Li(2022),"Hierarchical forecasting with a top-down alignment of independent level forecasts",International Journal of Forecasting. Vol. 38(4), pp. 1405-1414.(字母顺序排序,通讯作者)

[21].Fotios Petropoulos,...,Feng Li,et al(2022),"Forecasting: theory and practice",International Journal of Forecasting. Vol. 38(3), pp. 705-871.(高被引论文)

[20].Thiyanga S. Talagala,Feng Li and Yanfei Kang (2022),"FFORMPP: Feature-based forecast model performance prediction",International Journal of Forecasting. Vol. 38(3), pp. 920-943.

[19].Yanfei Kang, Wei Cao, Fotios Petropoulos and Feng Li(2022),"Forecast with Forecasts: Diversity Matters",European Journal of Operational Research. Vol. 31(1), pp. 180-190.(通讯作者)

[18].Xuening Zhu,Feng Li and Hansheng Wang (2021),"Least-Square Approximation for a Distributed System",Journal of Computational and Graphical Statistics. Vol. 30(4), pp. 1004-1018.(通讯作者)

[17].Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis,Feng Li and Vassilios Assimakopoulos (2021),"Déjà vu: A data-centric forecasting approach through time series cross-similarity",Journal of Business Research. Vol. 132(2021), pp. 719-731.(通讯作者)

[16].Megan G. Janeway, Xiang Zhao, Max Rosenthaler, Yi Zuo, Kumar Balasubramaniyan, Michael Poulson, Miriam Neufeld, Jeffrey J. Siracuse, Courtney E. Takahashi, Lisa Allee, Tracey Dechert, Peter A. Burke,Feng Li and Bindu Kalesan (2021),"Clinical diagnostic phenotypes in hospitalizations due to self-inflicted firearm injury",Journal of Affective Disorders. Vol. 278, pp. 172-180.

[15].康雁飞、李丰(2020),"预测:方法与实践"在线出版.

[14].康雁飞、李丰(2020),"统计计算"在线出版.

[13].Bindu Kalesan, Siran Zhao, Michael Poulson, Miriam Neufeld, Tracey Dechert, Jeffrey J. Siracuse, Yi Zuo and Feng Li(2020),"Intersections of firearm suicide, drug-related mortality, and economic dependency in rural America",Journal of Surgical Research. Vol. 256, pp. 96-102.(Last Author)

[12].Xixi Li, Yanfei Kang and Feng Li(2020),"Forecasting with time series imaging",Expert Systems with Applications. Vol. 160, pp. 113680.(通讯作者)

[11].Chengcheng Hao,Feng Li and Dietrich von Rosen (2020),"A Bilinear Reduced Rank Model", InContemporary Experimental Design, Multivariate Analysis and Data Mining. Springer Nature.

[10].Yanfei Kang, Rob J. Hyndman and Feng Li(2020),"GRATIS: GeneRAting TIme Series with diverse and controllable characteristics",Statistical Analysis and Data Mining. Vol. 13(4), pp. 354-376.(字母顺序排序,通讯作者)

[9].Hannah M. Bailey, Yi Zuo,Feng Li, Jae Min, Krishna Vaddiparti, Mattia Prosperi, Jeffrey Fagan, Sandro Galea and Bindu Kalesan (2019),"Changes in patterns of mortality rates and years of life lost due to firearms in the United States, 1999 to 2016: A joinpoint analysis",PLoS One. Vol. 14(11)

[8].Feng Li and Zhuojing He (2019),"Credit risk clustering in a business group: which matters more, systematic or idiosyncratic risk?",Cogent Economics & Finance. , pp. 1632528.(第一作者)

[7].Elizabeth C. Pino, Yi Zuo, Camila Maciel De Olivera, Shruthi Mahalingaiah, Olivia Keiser, Lynn L. Moore,Feng Li, Ramachandran S. Vasan, Barbara E. Corkey and Bindu Kalesan (2018),"Cohort profile: The MULTI sTUdy Diabetes rEsearch (MULTITUDE) consortium",BMJ Open. Vol. 8(5), pp. e020640.

[6].Feng Li and Yanfei Kang (2018),"Improving forecasting performance using covariate-dependent copula models",International Journal of Forecasting. Vol. 34(3), pp. 456-476.(第一作者)

[5].李丰(2016),"大数据分布式计算与案例"中国人民大学出版社.

[4].Feng Li(2013),"Bayesian Modeling of Conditional Densities". Thesis at:Department of Statistics, Stockholm University.

[3].Feng Li and Mattias Villani (2013),"Efficient Bayesian Multivariate Surface Regression",Scandinavian Journal of Statistics. Vol. 40(4), pp. 706-723.(第一作者)

[2].Feng Li, Mattias Villani and Robert Kohn (2011),"Modeling Conditional Densities Using Finite Smooth Mixtures", InMixtures: estimation and applications. , pp. 123-144. John Wiley & Sons Inc, Chichester.(第一作者)

[1].Feng Li, Mattias Villani and Robert Kohn (2010),"Flexible modeling of conditional distributions using smooth mixtures of asymmetric student t densities",Journal of Statistical Planning and Inference. Vol. 140(12), pp. 3638-3654.(第一作者)

主要讲授课程

·统计计算(中央财经大学精品实验课)

·大数据分布式计算(I, II)(应用统计大数据专业、数据科学与大数据专业核心课程)

·Python程序设计与数据挖掘(MBA、金融、会计核心课程)

·数据科学工具(中央财经大学核心通识课)

学术兼职

·2022—今 北京统计学会理事

·2023—今 中国土木工程学会工程风险与保险研究分会理

·2014—今 中国统计教学学会高等教育分会副秘书长

评审兼职

·国家外国专家项目评审专家

·联合国大数据竞赛导师与评审专家

·教育部学位论文评审专家

·全国应用统计专业学位研究生案例大赛评审专家

·担任JBES,IJF, Omega,PR,CSDA, Neurocomputing,《数理统计与管理》等国际国内期刊审稿人

部分受邀学术报告

· The 2023 ICSA China Conference, June 30 – July 3, 2023, Sichuan, China

·The41stInternational Symposium on Forecasting,27-28June, 2021.

·The 2021World Meeting of the International Society for Bayesian Analysis, Jun28—July 2, 2021.

·The40thInternational Symposium on Forecasting,26-28Oct, 2020.

·Twelfth International Conference on Monte Carlo Methods and Application (MCM 2019), Sydney, Australia, July 8-12, 2019.

·The39thInternational Symposium on Forecasting, 16-19 June in Thessaloniki, Greece.

·IMS-China International Conference on Statistics and Probability, June 28 – July 1, 2017, Nanning, China.

·The 1stInternational Conference on Econometrics and Statistics, Hong Kong, 15-17 June 2017.

·The 2016 World Meeting of the International Society for Bayesian Analysis, Jun 13—17, 2016, Sardinia, Italy.

【组织学术会议】

·The 2017 Beijing Workshop on Forecasting

·中国数量经济学会2016年年会

·2014年金融工程与风险管理国际研讨会

学术访问

·2014年8月  加拿大多伦多大学

·2013年10月  瑞典斯德哥尔摩大学

·2011年9月—2012年3月  瑞典林雪平大学

·2011年6月  英国南安普顿大学

·2009年5月  荷兰伊拉斯姆斯大学

荣誉与奖励

·第二届全国高校经管类实验教学案例大赛二等奖,2017年12月

·瑞典皇家统计学会Cramér 奖(最佳博士奖),2014 年 3 月。

·国际贝叶斯学会青年奖励基金,2012 年 6 月。

·瑞典Knut & Alice Wallenberg 基金奖励,2011 年 8 月。

·北京市级优秀毕业生,2007年 7 月。

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