Professor Steven Xiaogang Wang

Certified Professional Statistician by SSC.

Email: stevenw@yorku.ca

Please note that my previous email address stevenw@mathstat.yorku.ca is no longer used or checked due to email server migration.

Research Areas

Machine Learning, Data Mining, High dimensional optimization , Big Data with Application to Medicine, Disease modelling and Statistical Inference.

Education Background

Postdoc in Data Mining, Pacific Institute of Mathematical Sciences, 2002.

Ph.D. in Statistics, University of British Columbia, 2001.

M.Sc. in Applied Statistics, University of California at Riverside.

B.Sc in Computational Mathematics, Beijing University of Technology.

Selected Publication

Most Recent Publications (last 6 years)

Zana Rashidi, Kasra Ahmadi, Aijun An and Xiaogang Wang (2020). Adaptive Momentum Coefficient for Neural Network Optimization, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'20).

Lin, Y. Wang, X. and Wu, Y. (2020) A Segmented Generalized Markov Regime-Switching Model with Its Application in Financial Time Series Data.  Journal of Statistical Computation and Simulation. Accepted.

Pengjun Zhou, Ziyao, Dandan Xu, Ying Wang, Qi Bai, Yue Feng, Guifeng Su, Pengxiao Chen, Yao Wang, Huizhong Liu, Xiaogang Wang, Rong Zhang and Yifei Wang. (2019). Cepharanthine Hydrochloride Improves Cisplatin Chemotherapy and Enhances Immunity by Regulating Intestinal Microbes in Mice.  Frontier in Cellular and Infection Microbiology.

Yuejiao Fu, Yukun Liu, Hsiao-Hsuan Wang and Xiaogang Wang (2019).
Empirical likelihood estimation in multivariate mixture models with repeated measurements.  Statistical Theory and Related Fields. In Press.

Chen, L, Zhu, H. and Wang, X. (2018) Modelling Spatial-Temporal Distribution of Mosquito Abundance with Unobservable Environmental Factors. Journal of Medical Entomology. Accepted.

Li, X., Fu, Y., Wang, X., Demeo, D.L., Tantisira, K.,Weiss, S. and Qiu, W. (2018). Detecting Differentially Variable MicroRNAs via Model-based Clustering. International Journal of Genomics. Accepted.

Fok, R., An,A, Rasheid, Z., and Wang, X. (2018) Decoupling the Layers in Residual Networks, International Conference of Learning Representations (ICLR), 2018. Accepted.

Li, X. Fu, Y., Wang, X. and Qiu, W. (2018).Robust Joint Tests in the Application of DNA methylation data analysis. BMC Bioinformatics. To Appear.

Gold, N, Frasch, M., Herry C. , Richardson B and Wang, X. (2018). A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signal. Frontiers in Physiology- Computational Physiology and Medicine. To Appear.

Fok, R., An, A. and Wang, X. (2017). Geodesic and Contour Optimization using Conformal Mapping. Journal of Global Optimization. 69(1): 23-44. 

Wang, X., Qiu, X. and Wu, J. (2016). Convergence and Stability Analysis of Mean-shift Type Algorithm on Large Data Sets. Statistics and Its Interface.

Li, X., Jankowski, H., Boonpatcharanon, S., Tran, V., Wang, X. and Heffernan, J.M. (2015). Clustering Neuraminidase Influenza Protein Sequences, Proceedings of the International Symposium on Mathematical and Computational Biology. BIOMAT 2015.

Li, X., Qiu, W., Morrow, J., Weiss, J., Fu, Y. and Wang, X. (2015). A Comparative Study of Tests for Homegeneity of Variances with Application to DNA Methylation Data, PLoS One.

Wang, Q., Gold, N., Frasch, M., Huang, H.  and Wang, X. (2015). Mathematical Model of Cardiovascular and Metabolic Responses to Umbilical Cord Occulsions in Fetal Sheep. Bulletin of Mathematical Biology.

Fok, R., An, A. and Wang, X. (2015).Mining Evolving Data Streams with Particle Filers.  Computer Intelligence.

Wang, X., Wang, J. Russel, C.m Proctor, P., Bellod, R. Higuchi, K. and Zhu, H. (2014). Clustering of Abundance of West Nile Virus Vector Mosquitoes in Peel Region, Ontario. Environmental and Ecological Statistics.

Wang. X.,Durosier, D, Ross, M. Richardson, S., Frasch, M. (2014). Online Detection of Fetal Academia During Labor by Testing Synchronization of EEG and Heart Rate: A prospective study in fetal sheep. PLoS One.

Chen, S. and Wang. X. (2014). Approximate Risk Analysis using Numerical Integration on Sparse Grid. Journal of Mathematical and Computational Sciences.

 

 

Earlier Publications (Most Signifiant Ones)

Andreopoulos, B., An, A., Wang, X., Faloutsos, M and Schroeder, M. (2007). Clustering by Common Friends Finds Locally Significant Proteins Mediating Modules. Bioinformatics, Oxford University Press, 23(9): 1124-1131.

 Wang, X., Liang, D, Feng, X. and Ye, L. (2007). A Derivative Free Optimization Algorithm based on Conditional Moments. Journal of Mathematical Analysis and Applications. Vol. 331, No. 2, 1337 - 1360.

Wang, X. (2006). Approximating Bayesian Inference by Weighted Likelihood Method. The Canadian Journal of Statistics. Vol. 34,  279-298.

Wang, X., Qiu, W. and Zamar, R. (2006). An Iterative Non-parametric Clustering Algorithm Based on Local Shrinking. Computational Statistics and Data Analysis.

Zhang, P., Wang, X. and Song, P.X. (2006) Clustering Categorical Data Based on Distance Vectors. The Journal of the American Statistical Association. Vol. 101. No. 473, 355-367.

Wang, X. and Zidek, J.V. (2005). Derivation of Mixture Distribution and Weighted Likelihood as minimizers of KL-divergence subject to constraints. The Annals of the Institute of Statistical Mathematics. Vol 57, 687-701.

 Wang, X. and Zidek, J.V. (2005). Selecting likelihood weights by cross-validation. The Annals of Statistics. Vol., 33. No. 2, 463-500. 

 Wang, X., van Eeden, C. and Zidek, J.V. (2004). Asymptotic Properties of Weighted Likelihood Estimators.Journal of Statistical Planning and Inference. Vol 119, pp. 37-54.