Big Data and Statistical Learning
Fang, L., Cheng, X., Wang, H. and Yang, L. (2019). Idle Time Window Prediction in Cellular Networks with Deep Spatiotemporal Modeling. IEEE Journal on Selected Areas in Communications, 37, 1441-1454.
Fang, L., Cheng, X., Wang, H. and Yang, L. (2018). Mobile Demand Forecasting via Deep Graph-Sequence Spatiotemporal Modeling in Cellular Networks. IEEE Internet of Things Journal, 5, 3091-3101.
Fang, L., Cheng, X., Yang, L. and Wang, H. (2018). Location Privacy in Mobile Big Data: User Identifiability via Habitat Region Representation. Journal of Communications and Information Networks, 3, 31-38.
Sienkiewicz, E., Song, D., Breidt, F.J. and Wang, H. (2017). Sparse Functional Dynamical Models --- a Big Data Approach. Journal of Computational and Graphical Statistics, 26, 319-329.
R packages:
- Big Data: Maximum Likelihood Estimate and Regularized MLE for Generalized Linear Models bdglm.
- Big Data: Functional Dynamic Multiple-Input Single-Output Models for Neural Spikes bdmiso, installation instructions.
B.S., Nankai University, Tianjin, China
Ph.D., University of North Carolina, Chapel Hill
Object Oriented Data Analysis
Spatial Statistics
Information Fusion
Statistical Analysis on Networks
Computational Neuroscience
216 Statistics Building
Department of Statistics
Colorado State University
Fort Collins, CO80523
Email: wanghn@stat.colostate.edu
Voice: 970-491-2449
My research has been supported by NSF grants DMS-0706761, DMS-0854903, DMS-1106975, DMS-1521746, DMS-1737795, DMS-1923142, CNS-1932413 and DMS-2123761 as well as grants with other collaborators.