3rd International Conference on Statistics: Theory and Applications (ICSTA’21)
Due to COVID'19 pandemic it will be done VIRTUALLY
The keynote speakers for the 3rd International Conference on Statistics: Theory and Applications (ICSTA'21) will be announced shortly! Thank you for your patience.
Dr. Michael Evans
University of Toronto, Canada
Topic of Keynote:
Dr. Faming Liang
Purdue University, USA
Topic of Keynote: Consistent Sparse Deep Learning: Theory and Computation
Dr. Jiahua Chen
University of British Columbia, Canada
Dr. Jiahua Chen received his Master’s degree from the Institute of System’s Science in Academia Sinica in Jan 1985 under the supervision of Professor Ping Cheng, and Ph. D. degree from the University of Wisconsin-Madison in July 1990 under the supervision of Professor Jeff Wu.
Dr. Jiahua Chen joined the Department of Statistics and Actuarial Science at the University of Waterloo as a visiting scholar in the year 1989, accepted an assistant professorship in 1991, and was dutifully promoted to associate and full professor during the period until the end of 2006. He then joined the Department of Statistics at the University of British Columbia as Canada Research Chair, Tier I from Jan 2007 until Dec 2020 from which point he remains as a full professor. He worked on problems in the design of experiment, but his research interest quickly extends broadly to include Finite Mixture Models, Empirical Likelihood, Survey Methodology, and many others. He is proud of his result on the periodicity of the minimum aberration fractional factorial designs, the groundbreaking EM-test for the order of finite mixture models, the challenging results on the nearest neighbor imputation in sampling data analysis, the pioneering work of introducing the empirical likelihood to sampling problems, as well as the invention of extended Bayesian information criterion for large model spaces.
Dr. Jiahua Chen is an elected fellow of the Institute of Mathematical Statistics and the American Statistical Association. He is the recipient of the CRM-SSC Prize in Statistics for his outstanding contributions to the statistical sciences. This prestigious award, jointly sponsored by the Statistical Society of Canada(SSC) and the Centre de recherches mathématiques de Montréal (CRM), is given each year to a Canadian statistician in recognition of outstanding contributions to the discipline during the recipient’s first 15 years after earning a doctorate. He received the Gold Medal, the top prize of the Statistical Society of Canada in 2014, the International Chinese Statistical Association distinguished achievement award in 2016.
Topic of Keynote: Distributed Learning of Finite Gaussian Mixtures
Dr. Xiaoming Huo
Georgia Institute of Technology, USA
Topic of Keynote: A Statistical Analysis of Deep Learning and Its Related Techniques