Research

Publication List

Research Profile on Google Scholar

  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

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

Recent Presentations and Talks

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

Other Academic Profiles

My mathematics genealogy