李丰

李丰,中央财经大学统计与数学学院副院长,大数据分析专业硕士导师,中国统计教育学会高等教育分会会副秘书长。博士毕业于瑞典斯德哥尔摩大学,研究领域包括贝叶斯计算,统计预测,分布式学习等。曾获瑞典皇家统计学会 Cramér 奖,国际贝叶斯学会青年奖励基金, 瑞典 Knut & Alice Wallenberg 基金奖励,第二届全国高校经管类实验教学案例大赛二等奖。主持和参与多项国家自然科学基金项目。著有《Bayesian Modeling of Conditional Densities》和《大数据分布式计算与案例》,研究成果发表在人工智能与数据挖掘期刊 Expert Systems with ApplicationsStatistical Analysis and Data Mining,统计期刊 Scandinavian Journal of StatisticsJournal of Statistical Planning and Inference,预测期刊International Journal of Forecasting,医学期刊 Journal of Surgical ResearchBMJ Open等。

工作单位

中央财经大学统计与数学学院,副院长,硕士研究生导师

联系方式

网    页:https://feng.li/
电子邮箱:feng.li@cufe.edu.cn
办公电话:+86-(0)10-6177-6189 
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)1号学院楼210房间

教育背景

简历

研究兴趣

  • 贝叶斯计算 | 计量经济与预测方法 | 分布式学习

科研项目

  • 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,结项。
  • 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。2014/01-2017/12、项目负责人,结项。
  • 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、在研、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、在研、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、在研、参加。

发表论文

  1. Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Feng Li*, Nikolaos Athiniotis, and Vassilios Assimakopoulos. (2020). Déjà vu: A data-centric forecasting approach through time series cross-similarity, Journal of Business Research.
  2. Xixi Li, Yanfei Kang, and Feng Li*. (2020). Forecasting with time series imaging, Expert Systems with Applications. 160(1)
  3. Megan GJaneway, Xiang Zhao, Max Rosenthaler, Yi Zuo, Kumar Balasubramaniyane, Michael Poulson, Miriam Neufeld, Jeffrey J. Siracuse, Courtney E. Takahashif, Lisa, Allee, Tracey Dechert, Peter A Burke, Feng Li, and Bindu Kalesan (2020). Clinical diagnostic phenotypes in hospitalizations due to self-inflicted firearm injury, Journal of Affective Disorders. (In Press).
  4. Bindu Kalesan, Siran Zhao, Michael Poulson, Miriam Neufeld, Tracey Dechert, Jeffrey J Siracuse, Yi Zuo, and Feng Li (2020). Intersections between firearm suicide, drug mortality and economic dependency in rural America, Journal of Surgical Research. 256, pp 96-102. Journal’s Cover Paper.
  5. Chengcheng Hao, Feng Li, and Dietrich von Rosen. (2020). A Bilinear Reduced Rank Model, Book chapter in Contemporary Experimental Design, Multivariate Analysis and Data Mining (Jianqing Fan and Jianxin Pan eds.), Springer.
  6. Yanfei Kang, Rob Hyndman, and Feng Li*. (2020). GRATIS: GeneRAting TIme Series with diverse and controllable characteristics, Statistical Analysis and Data Mining. 13(4), pp. 354-376.
  7. 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 14(11): e0225223.
  8. 康雁飞、李丰(译)(2019). 预测:方法与实践(第2版)(Hyndman & Athanasopoulos 著. Forecasting: Principles and Practice)
  9. Feng Li and Zhuojing He. (2019). Credit Risk Clustering in a Business Group: Which Matters More, Systematic or Idiosyncratic Risk? Cogent Economics and Finance, 7(1632528).
  10. Feng Li and Yanfei Kang (2018) Improving forecasting performance using covariate-dependent copula models, International Journal of Forecasting34(3), pp. 456-476.
  11. 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, 8(5): e020640.
  12. Feng Li (2016). 大数据分布式计算与案例(Distributed Statistical Computing for Big Data and Case Studies), ISBN:9787300230276
  13. Feng Li. (2013). Bayesian Modeling of Conditional Densities. Ph.D. thesis, Department of Statistics, Stockholm University. ISBN: 978-91-7447-665-1
  14. Feng Li and Mattias Villani. (2013). Efficient Bayesian Multivariate Surface Regression, Scandinavian Journal of Statistics, 40(4), pp. 706-723
  15. Feng Li, Mattias Villani, and Robert Kohn. (2011). Modeling Conditional Densities using Finite Smooth Mixtures, Book chapter in Mixture Estimation and Applications (Mengersen, K.L., Robert, C. P. and Titterington, D.M. eds), Wiley.
  16. 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, 140(12), pp. 3638-3654

受邀学术报告

  1. ICSA Conference on Data Science, January 11-13, 2019, Xishuangbanna, China.
  2. School of Data Science, Fudan University, Oct 28-30, 2017, Shanghai, China
  3. IMS-China International Conference on Statistics and Probability, June 28 – July 1, 2017, Nanning, China.
  4. The 1st International Conference on Econometrics and Statistics, Hong Kong, 15-17 June 2017.
  5. The 2016 World Meeting of the International Society for Bayesian Analysis, Jun 13—17, 2016, Sardinia, Italy.
  6. IMS-China International Conference on Statistics and Probability, June 1-4, 2015, Kunming, China.
  7. International Symposium on Financial Engineering and Risk Management 2014, June 27, 2014, Beijing, China.
  8. Guanghua School of Management, Peking University, Oct 14, 2013, Beijing, China
  9. The Stockholm University Forskardagarna, 2-3 Oct, 2013, Stockholm, Sweden.
  10. The 59th World Statistics Congress, August 25-29, 2013, Hong Kong.
  11. The 2012 World Meeting of the International Society for Bayesian Analysis, Jun 25—29, 2012, Japan.
  12. The third Linnaeus University Workshop in Stochastic Analysis and Applications, May 24—25, 2012, Växjö, Sweden.
  13. Workshop on “Analysis of High-Dimensional Data”, Jönköping International Business School, Feb 16—17, 2012, Sweden.
  14. The LiU Seminar Series in Statistics and Mathematical Statistics, Linköping University, Oct 11, 2011, Sweden.
  15. The 42nd Winter Conference in Statistics — Incomplete data: semi-parametric and Bayesian methods, Mar 6—10, 2011, Sweden.
  16. The 2010 World Meeting of the International Society for Bayesian Analysis, Jun 3—8, 2010, Spain.

学术兼职

  • 2018—今    全国工业统计学教学研究会常务理事
  • 2014—今     中国统计教学学会高等教育分会副秘书长
  • 期刊审稿人 (Journal of Business and Economic Statistics, International Journal of Forecasting, Journal of Official Statistics, Quantitative Finance, Information Sciences)

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。

访谈