活动报名 | 第三届北大-清华统计论坛

2018-05-10

第三届北大清华统计论坛
2018 Peking-Tsinghua Joint Statistics Colloquium

        为了继续传承和弘扬北大清华两校教师以及学生之间的友好合作和学术交流,推动大数据背景下统计理论和应用的时代大发展,北京大学统计科学中心再次携手清华大学统计学研究中心,于2018年06月03日下午北京大学光华管理学院1号楼201室举办“第三届北大–清华统计论坛”。

特邀报告:

周晓华    北京大学讲席教授、国家“千人计划”入选专家

研究方向:

缺失数据,因果推断分析, 大数据分析,半参数模型, 医学检验, 脑科学,卫生经济,卫生服务领域发展新的统计方法

报告题目:

Statistical Methods in Precision Medicine

 

 

 

 

杨立坚    清华大学教授、国家“千人计划”入选专家

研究方向:

时间序列,函数型及高维数据的统计推断,以及统计学对经济学、金融学、农学、食品科学、地理学和遗传学的应用

报告题目:

Generalized Additive Model: Theory, Methods and Applications over Thirty Years

 

 

主办方

  • 北京大学统计科学中心
  • 清华大学统计学研究中心

 

参会人员请点击以下链接或扫描二维码填写报名表格,以便会议组织机构统计人数,谢谢!

cn.mikecrm.com/K5AkNmI

 

第三届北大-清华统计论坛

2018 年 6 月 3 日 · 北京

会议地点: 北京大学光华管理学院1号楼201室

 

时间 议 程
13:00-13:30 注册时间
13:30-13:40 开幕仪式
13:40-14:40 周晓华教授

 

Statistical Methods in Precision Medicine

14:40-15:00 茶  歇
 

 

15:00-16:00

杨立坚教授

 

Generalized Additive Model: Theory, Methods and Applications over Thirty Years

16:00-16:10 合影
16:10-17:00 海报展示
17:00-17:10 颁奖

 

特邀报告(一)

TitleStatistical Methods in Precision Medicine

Speaker: Prof. Xiao-Hua Zhou

Abstract:

According to the U.S. National Institutes of Health (NIH), precision medicine is “an emerging practice of medicine that uses an individual’s genetic profile to guide decisions made in regard to the prevention, diagnosis, and treatment of disease”. Stimulated by the advancements in fields such as genomics and medical imaging, the last decade has witnessed exciting and remarkable progress in precision medicine, ranging from treating breast cancer to treating major depressive disorder. The success of precision medicine crucially depends on the development of accurate and reliable statistical tools for estimating the optimal treatment regime given the data collected from clinical trials or observational studies.  In this talk, I will discuss two main statistical frameworks in precision medicine. One is based on predictive biomarkers and associated covariate specific treatment effect curves, and another is based on deriving optimal individualized treatment rules (ITRs).

About the Speaker:

Xiao-Hua Zhou is PKU Endowed Professor at Peking University and Director of Center for Data Science in Chinese Medicine of Beijing Institute of Big Data Research, and Associate Director of Peking University Center for Data Science in Health and Medicine.  Dr. Zhou was Professor in the Department of Biostatistics at University of Washington between 2003 and 2018.  He was elected to a Fellow of the American Statistical Association in 2004 and a Fellow of the American Association for Advancement of Science (AAAS) in 2016. In 2007, he received a prestigious Research Career Scientist Award from the United States Federal Government.

Dr. Zhou has made important contributions in developing new statistical methods in medicine and public health. Specifically, Dr. Zhou has developed new statistical methods for (1) Diagnostic Medicine; (2) Health Economics; (3) Causal Inferences in Broken Clinical Trials and Observational Studies; and (4) Precision Medicine.  Dr. Zhou has published over 230 SCI papers and is either the corresponding author or senior author on most of them; many of them have been published in top statistical journals, such as Journal of the Royal Statistical Society Series B (JRSS B), Journal of the American Statistical Association (JASA), Biometrics, Biometrika, Annals of Statistics, and Statistics in Medicine. He served as Chair of the Section on Statistics in Epidemiology of the American Statistical Association, Chair of the Health Policy Statistics Section of the American Statistical Association, and Chair of the Mental Health Statistics Section of the American Statistical Association.  He is currently President of International Biometric Society (IBS) – Chinese Region (IBS-China) and President of Biostatistics and Medical Statistical Section of China Applied Statistical Association. He was an Associate Editor for Statistical Sinica and Biometrics.  He is currently an Associate Editor for Statistics in Medicine and an Associate Editor for the Journal of the American Statistical Association - Theory and Methods Section.   He is also Editor in Chief for Biostatistics & Epidemiology, the official journal of IBS-China. In 2002, along with the other two scholars, Dr. Zhou published the first comprehensive statistical textbook in diagnostic medicine with Wiley & Sons, entitled  "Statistical Methods in Diagnostic Medicine"; the second edition of the book was published in 2012. In 2014, along with his three former students, Dr. Zhou published another book with Wiley & Sons, entitled “Applied Missing Data Analysis in the Health Sciences”.

 

特邀报告(二)

Title: Generalized Additive Model: Theory, Methods and Applications over Thirty Years

Speaker: Prof. Lijian Yang

Abstract:

The 1984 Stanford University Biostatistics Division Technical Report of Hastie & Tibshirani (1984) introduced the concept and term “generalized additive model (GAM)”, which has been popularized by Hastie & Tibshirani (1986 Statistical Science), and Hastie & Tibshirani (1990 Chapman and Hall, 15306 Google Scholar citations). GAM has since found wide applications from environmental studies to predictive policing, from credit rating to survival analysis. I will discuss the statistical theory for GAM, the development of which reflects the diversity of statistics as a discipline over the past 30 years. Some interesting real-life applications of GAM are also presented. About the Speaker:

Lijian Yang received B.S. in Mathematics from Peking University (1987), Ph.D. in Statistics from University of North Carolina (1995), and did postdoc work at Humboldt Universität zu Berlin (1997). He was Assistant Professor (1997-2001), Tenured Associate Professor (2001-06), Tenured Full Professor (2006-14), and Graduate Director (2007-10) at Michigan State University. He is an elected Fellow of the American Statistical Association, of the Institute of Mathematical Statistics, and of the International Statistical Institute. He was awarded the Tjalling C. Koopmans Econometric Theory Prize by Yale University Press, and selected as Overseas Leading Creative Talent (1000 Talent) in China. Lijian Yang has published over 60 SCI/SSCI articles in Annals of StatisticsAnnals of ProbabilityJournal of EconometricsJournal of the American Statistical AssociationJournal of the Royal Statistical Society BJournal of Applied EconometricsEconometric TheoryBioinformatics, etc., on dimension reduction, time series, functional data, econometrics, food science, agronomy, etc.

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