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Yanfei Kang, Ph.D
Associate Professor 
School of Economics and Management 
Beihang University 
Beijing 100191 China
 
Email: yanfeikang@buaa.edu.cn 
Please feel free to contact me or visit my KLLAB.org if you are interested in my research areas!

Research Interests

  • Forecasting
  • Statistical Computing
  • Big Data and Machine Learning

Education

Positions

  • November 2016 – Present, Associate Professor, School of Economics and Management, Beihang University.
  • August 2015 – August 2016, Senior R&D Engineer, Big Data Group, Baidu Inc.
  • August 2014 – July 2015, Postdoc Research Fellow, Monash University, Australia.

Working papers

  1. Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babai, M.Z., Barrow, D.K., Bergmeir, C., Bessa, R.J., Boylan, J.E., Browell, J., Carnevale, C., Castle, J.L., Cirillo, P., Clements, M.P., Cordeiro, C., Cyrino Oliveira, F.L., De Baets, S., Dokumentov, A., Fiszeder, P., Franses, P.H., Gilliland, M., Gönül, M.S., Goodwin, P., Grossi, L., Grushka-Cockayne, Y., Guidolin, M., Guidolin, M., Gunter, U., Guo, X., Guseo, R., Harvey, N., Hendry, D.F., Hollyman, R., Januschowski, T., Jeon, J., Jose, V.R.R., Kang, Y., Koehler, A.B., Kolassa, S., Kourentzes, N., Leva, S., Li, F., Litsiou, K., Makridakis, S., Martinez, A.B., Meeran, S., Modis, T., Nikolopoulos, K., Önkal, D., Paccagnini, A., Panapakidis, I., Pavía, J.M., Pedio, M., Pedregal Tercero, D.J., Pinson, P., Ramos, P., Rapach, D., Reade, J.J., Rostami-Tabar, B., Rubaszek, M., Sermpinis, G., Shang, H.L., Spiliotis, E., Syntetos, A.A., Talagala, P.D., Talagala, T.S., Tashman, L., Thomakos, D., Thorarinsdottir, T., Todini, E., Trapero Arenas, J.R., Wang, X., Winkler, R.L., Yusupova, A., Ziel, Z. (2020). Forecasting: theory and practice. Working paper.
  2. Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir (2020). Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation (under review). Working paper.
  3. Xiaoqian Wang, Yanfei Kang, Rob Hyndman, Feng Li (2020). Distributed ARIMA models for ultra-long time series (under review). Working paper. Spark implementation.
  4. Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos, Feng Li (2020). Que será será? The uncertainty estimation of feature-based time series forecasts  (under review). Working paper.
  5. Thiyanga S. Talagala, Feng Li, Yanfei Kang (2019). FFORMPP: Feature-based forecast model performance prediction (under review). Working paper. R package.

Publications

  1. Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis, Feng Li, Vassilios Assimakopoulo (2020). Déjà vu: A data-centric forecasting approach through time series cross-similarity (in press), Journal of Business Research. Online. Working paper. Online app.
  2. Xixi Li, Yanfei Kang, Feng Li (2020). Forecasting with time series imaging, Expert Systems with Applications 160: 113680, doi: 10.1016/j.eswa.2020.113680. Online. Working paper. Code.
  3. Yanfei Kang, Rob J Hyndman, Feng Li (2020). GRATIS: GeneRAting TIme Series with diverse and controllable characteristics, Statistical Analysis and Data Mining 13(4): 354-376, doi: 10.1002/sam.11461. Online. Working paper. R package. Shiny app.
  4. Yitian Chen, Yanfei Kang*, Yixiong Chen, Zizhuo Wang (2020). Probabilistic Forecasting with Temporal Convolutional Neural Network, Neurocomputing 399: 491-501, doi:10.1016/j.neucom.2020.03.011. Online. Code.
  5. 康雁飞、李丰（2019 译）. 预测：方法与实践（第二版）（Hyndman & Athanasopoulos 著. Forecasting: Principles and Practice）. 在线版本.
  6. Feng Li, Yanfei Kang* (2018). Improving forecasting performance using covariate-dependent copula models, International Journal of Forecasting 34(3): 456-476, doi:10.1016/j.ijforecast.2018.01.007. Online.
  7. Yanfei Kang*, Rob J. Hyndman, Kate Smith-Miles. (2017). Visualising Forecasting Algorithm Performance using Time Series Instance Space. International Journal of Forecasting 33(2): 345–358, doi: 10.1016/j.ijforecast.2016.09.004. Online.
  8. Yanfei Kang, Danijel Belusic, Kate Smith-Miles. (2015). Classes of Structures in the Stable Atmospheric Boundary Layer. Quarterly Journal of the Royal Meteorological Society 141(691): 2057–2069, doi: 10.1002/qj.2501. Online. R package.
  9. Yanfei Kang. (2015). Detection, classification and analysis of events in turbulence time series. Bulletin of the Australian Mathematical Society 91(3): 521-522, doi: 10.1017/S0004972715000106. Online.
  10. Yanfei Kang, Danijel Belusic, Kate Smith-Miles. (2014). Detecting and classifying events in noisy time series. Journal of the Atmospheric Sciences 71(3): 1090–1104, doi: 10.1175/JAS-D-13-0182.1. Online.
  11. Yanfei Kang, Danijel Belusic, Kate Smith-Miles. (2014). A note on the relationship between turbulent coherent structures and phase correlation. Chaos: An Interdisciplinary Journal of Nonlinear Science 24(2) 023114: 1-6, doi: 10.1063/1.4875260. Online.
  12. Yanfei Kang, Danijel Belusic, Kate Smith-Miles. (2013). How to extract meaningful shapes from noisy time-series subsequences? In: Proceedings of the 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). IEEE, pp. 65–72, doi: 10.1109/CIDM.2013.6597219. Online.
  13. Yanfei Kang. (2012). Real-time change detection in time series based on growing feature quantization. In: Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 1–6, doi: 10.1109/IJCNN.2012.6252381. Online.

Awards

  • 100-Talent Program, by Beihang University, 2016.
  • Best New Employee, by Baidu, 2015.
  • Ph.D. scholarship for oversea studies, by Chinese Scholarship Council (CSC), 2010.
  • First Class Scholarship, by Renmin University of China, 2009.
  • Outstanding Graduate of Shandong University of Finance and Economics, 2009.
  • National Scholarship, by Ministry of Education of China, 2008.