Feng Li, Ph.D.

Assistant Professor, Associate Dean 
School of Statistics and Mathematics
Central University of Finance and Economics
100081 Beijing, China
Email: feng.li@cufe.edu.cn 
Phone: +86-(0)10-6228-8548 (Haidian Campus)
+86-(0)10-6177-6189 (Shahe Campus)

Education 🎓

Curriculum Vitae

Research interests👨‍🔬

  • Bayesian statistics
  • Econometrics and forecasting
  • Multivariate statistics
  • Complex models and big data

Working Papers⏳

  1. Déjà vu: forecasting with similarity (with Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis, and Vassilios Assimakopoulos)
  2. Least squares approximation for a distributed system (with Xuening Zhu and Hansheng Wang)
  3. FFORMPP: Feature-based forecast model performance prediction (with Thiyanga S. Talagala and Yanfei Kang)
  4. Que será será? The uncertainty estimation of feature-based time series forecasts (with Xiaoqian Wang, Yanfei Kang and Fotios Petropoulos)
  5. Forecasting with time series imaging (with Xixi Li and Yanfei Kang)
  6. GRATIS: GeneRAtion of TIme Series with diverse and controllable characteristics (with Yanfei Kang and Rob J. Hyndman)

Research Grants

Publications 🖺

  • Li, F., and He, Z. (2019) Credit Risk Clustering in a Business Group: Which Matters More, Systematic or Idiosyncratic Risk? Cogent Economics and Finance, 7(1632528).
    [Journal version | Working Paper | Appendix ]
  • Li, F., and Kang, Y.(2018). Improving forecasting performance using covariate-dependent copula models, International Journal of Forecasting, 34(3), pp. 456-476.
    [Journal’s versionWorking Paper | Paper on arXiv]
  • Li, F., Kalesan, B., Zuo, Y.  et. al (2018) Cohort Profile: The MULTI sTUdy Diabetes rEsearch (MULTITUDE) Consortium, BMJ Open, 8(5), pp. e020640.
    [Journal’s version]
  • Li, F. (2016). Distributed Statistical Computing for Big Data and Case Studies, ISBN:9787300230276
    [Available on JD.com and Amazon.cn]
  • Li, F. (2013). Bayesian Modeling of Conditional Densities. Ph.D. thesis, Department of Statistics, Stockholm University. ISBN: 978-91-7447-665-1
    [Link to DiVA | Fulltext]
  • Li, F, and Villani, M. (2013). Efficient Bayesian Multivariate Surface Regression, Scandinavian Journal of Statistics, 40(4), pp. 706-723.
    [Journal’s version | Working Paper | R package | Talk | Poster]
  • Li, F, Villani, M. and Kohn, R. (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.
    [Publisher’s version | Working Paper]
  • Li, F, Villani, M. and Kohn, R. (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.
    [Journal’s version | Working Paper | Talk | Poster]

Awards 🌟

  • The 2014 Cramér Prize, Mar 2014.
  • International Society for Bayesian Analysis junior travel award, Jun, 2012.
  • Travel grant from The Swedish Knut and Alice Wallenberg Foundation, Aug, 2011.
  • Outstanding graduate student, honored by Beijing Municipal Education Commission, Jul, 2007, China.