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

Selected Publications 🖺

  1. Bailey HM, Zuo Y, Li F, et al. (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.
  2. 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).
  3. Li, F., and Kang, Y.(2018). Improving forecasting performance using covariate-dependent copula models, International Journal of Forecasting, 34(3), pp. 456-476.
  4. Li, F., Kalesan, B., Zuo, Y.  et. al (2018) Cohort Profile: The MULTI sTUdy Diabetes rEsearch (MULTITUDE) Consortium, BMJ Open, 8(5): e020640.
  5. Li, F. (2016). Distributed Statistical Computing for Big Data and Case Studies, ISBN:9787300230276
  6. Li, F. (2013). Bayesian Modeling of Conditional Densities. Ph.D. thesis, Department of Statistics, Stockholm University. ISBN: 978-91-7447-665-1
  7. Li, F., and Villani, M. (2013). Efficient Bayesian Multivariate Surface Regression, Scandinavian Journal of Statistics, 40(4), pp. 706-723
  8. 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.
  9. 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

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.