中文主页
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!
News
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 under review
- Xiaoqian Wang, Rob Hyndman, Feng Li, Yanfei Kang (2022). Forecast combinations: an over 50-year review. Working paper.
- Bohan Zhang, Yanfei Kang, Anastasios Panagiotelis, Feng Li (2022). Optimal reconciliation with immutable forecasts. Working paper.
- Li Li, Yanfei Kang, Fotios Petropoulos, Feng Li (2022). Feature-based intermittent demand forecast combinations: bias, accuracy and inventory implications. Working paper.
- Li Li, Yanfei Kang, Feng Li (2021). Bayesian forecast combination using time-varying features. Working paper.
- Yun Bai, Ganglin Tian, Yanfei Kang*, Suling Jia (2021). A hybrid ensemble method with negative correlation learning for regression. Working paper.
Publications
- Xiaoqian Wang, Yanfei Kang, Rob Hyndman, Feng Li (2022). Distributed ARIMA models for ultra-long time series (in press). International Journal of Forecasting. Working paper. Spark implementation.
- Xixi Li, Fotios Petropoulos, Yanfei Kang* (2021). Improving forecasting by subsampling seasonal time series (in press). International Journal of Production Research. Online. Working paper.
- 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. (2021). Forecasting: theory and practice (in press). International Journal of Forecasting. Online. Working paper.
- Yanfei Kang, Wei Cao, Fotios Petropoulos, Feng Li (2021). Forecast with forecasts: Diversity matters. European Journal of Operational Research 301(1): 180-190, doi: 10.1016/j.ejor.2021.10.024. Online. Working paper.
- Xixi Li#, Yun Bai#, Yanfei Kang* (2021). Exploring the social influence of Kaggle virtual community on the M5 competition (in press). International Journal of Forecasting. Online. Working paper.
- Evangelos Theodorou#, Shengjie Wang#, Yanfei Kang*, Evangelos Spiliotis, Spyros Makridakis, Vassilios Assimakopoulos (2021). Exploring the representativeness of the M5 competition data (in press), International Journal of Forecasting, doi: 10.1016/j.ijforecast.2021.07.006. Online. Working paper.
- Thiyanga S. Talagala, Feng Li, Yanfei Kang* (2021). FFORMPP: Feature-based forecast model performance prediction (in press), International Journal of Forecasting, doi: 10.1016/j.ijforecast.2021.07.002. Online. Working paper. R package.
- Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir (2021). Improving the accuracy of global forecasting models using time series data augmentation, Pattern Recognition 120:108148, doi: 10.1016/j.patcog.2021.108148. Online. Working paper.
- Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos, Feng Li (2021). The uncertainty estimation of feature-based forecast combinations (in press), Journal of the Operational Research Society, doi: 10.1080/01605682.2021.1880297. Online. Working paper. R package.
- Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis, Feng Li, Vassilios Assimakopoulo (2021). Déjà vu: A data-centric forecasting approach through time series cross-similarity, Journal of Business Research 132: 719-731, doi: 10.1016/j.jbusres.2020.10.051. Online. Working paper. Online app.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.