Updates on 2017 ICSA China Conference at Jilin, China

Saturday, July 29, 2017

The 2017 ICSA China Conference with the Focus on Lifetime Data Science was successfully held on July 2 - July 5, 2017 in the beautiful Jilin City, Jilin Province, P.R. China. The conference, which had 2 keynote sessions and 24 invited sessions, attracted more than 120 researchers around the world. "The meeting had a focus on lifetime data science but attracted people from many other related areas," said Prof. Jianguo Sun, the Chair of the Scientific Committee of the 2017 ICSA China Conference at Jilin. "The ICSA leaders and local people did a ton of work, which was key for the success of the conference." Five young researchers (see below) were awarded the Junior Researcher Award ( http://sta.jlu.edu.cn/icsa-2017/?mod=info&act=view&id=30 ) that was sponsored by Biostatistics & Data Sciences Department at Boehringer Ingelheim (BI). The conference was organized by Jilin University and Beihua University with Prof. Dehui Wang and Prof. Yueting Yang being the Co-Chairs of the Local Organizing Committee.

Congratulations to the five recipients of the Junior Researcher Award:

Giorgos Bakoyannis, Indiana University, Fairbanks School of Public Health

and School of Medicine

(paper title: "Semiparametric Analysis of Competing Risks Data under Double-Sampling Designs")

Yang Li, University of North Carolina at Charlotte

(paper title: "Semiparametric varying-coefficient regression analysis of recurrent events")

Ling Ma, Clemson University, Clemson, SC

(paper title: "Joint modeling of functional data and time to event: an application to fecundity studies")

Peijie Wang, Center for Applied Statistical Research, School of Mathematics, Jilin University

(title paper: "Regression Analysis of Doubly Interval-Censored Failure Time Data with a Cured Subgroup")

Xue (Loya) Yang, Janssen Research & Development, Shanghai, China

(paper title: "Improve efficiency and reduce bias of Cox regression models for two-stage randomization designs using auxiliary covariates")

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