1. Xuening Zhu, Feng Li*, & Hansheng Wang (2021). Least squares approximation for a distributed system. Journal of Computational and Graphical Statistics. (in press).
  2. Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos, & Feng Li* (2021). The uncertainty estimation of feature-based forecast combinations, Journal of the Operational Research Society. (in press).
  3. Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis, Feng Li*, & Vassilios Assimakopoulo (2021). Déjà vu: A data-centric forecasting approach through time series cross-similarityJournal of Business Research. (in press).
  4. Xixi Li, Yanfei Kang,  & Feng Li* (2020). Forecasting with time series imagingExpert Systems with Applications 160: 113680.
  5. Yanfei Kang, Rob J Hyndman,  & Feng Li* (2020). GRATIS: GeneRAting TIme Series with diverse and controllable characteristicsStatistical Analysis and Data Mining 13(4): 354-376.
  6. Chengcheng Hao, Feng Li,  & Dietrich von Rosen (2020). A Bilinear Reduced Rank ModelIn Jianqing Fan and Jianxin Pan (eds.), Contemporary Experimental Design, Multivariate Analysis and Data Mining, Springer.
  7. Hyndman, R.J., & Athanasopoulos, G.著. 预测:方法与实践(第2版),康雁飞、李丰(译)
  8. Hannah M Bailey, Yi Zuo, Feng Li, Jae Min, Krishna Vaddiparti, Mattia Prosperi, Jeffrey Fagan, Sandro Galea,  & 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 analysisPLoS One, 14(11).
  9. Feng Li  & Zhuojing He (2019). Credit risk clustering in a business group: which matters more, systematic or idiosyncratic risk? Cogent Economics & Finance, page 1632528.
  10. Feng Li & Yanfei Kang (2018). Improving forecasting performance using covariate-dependent copula models. International Journal of Forecasting, 34(3):456–476.
  11. Elizabeth C Pino, Yi Zuo, Camila Maciel DeOlivera, Shruthi Mahalingaiah, Olivia Keiser, Lynn L Moore, Feng Li, Ramachandran S Vasan, Barbara E Corkey  & Bindu Kalesan (2018). Cohort profile: The multistudy diabetes research (multitude) consortiumBMJ Open, 8(5):e020640.
  12. 李丰(2016)大数据分布式计算与案例。中国人民大学出版社。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  & Mattias Villani (2013). Efficient Bayesian multivariate surface regressionScandinavian Journal of Statistics, 40(4):706–723.
  15. Feng Li, Mattias Villani  & Robert Kohn (2011.). Modeling conditional densities using finite smooth mixtures. In Kerrie Mengersen, Christian Robert, Mike Titterington (eds.), Mixtures: estimation and applications, pages 123–144. John Wiley & Sons Inc, Chichester.
  16. Feng Li, Mattias Villani  & Robert Kohn (2010). Flexible modeling of conditional distributions using smooth mixtures of asymmetric student t densitiesJournal of Statistical Planning and Inference,140(12):3638–3654

Research Grants

  • Development of the Methodologies of Objective Performance Criteria Based Single-Armed Trials for The Clinical Evaluation of Traditional Chinese Medicine. funded by National Natural Science Foundation of China, (2020-). Major Investigator.
  • Efficient Bayesian Flexible Density Methods with High Dimensional Financial Data funded by National Natural Science Foundation of China, (2016-2019). Principal investigator.
  • Bayesian Multivariate Density Estimation Methods for Complex Data funded by Ministry of Education, China (2014-2016). Principal investigator


PDF slides are available for download.

  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.

Recent academic visits

  • 2014 Aug, Toronto University, Canada
  • 2013 Oct, Stockholm University, Sweden
  • 2011 Sep – 2012 March, Linköping University, Sweden
  • 2011 June, University of Southampton, UK
  • 2009 May, Erasmus University Rotterdam, The Netherlands

My mathematics genealogy