Hongkai’s Research Group

Johns Hopkins - Nanjing Exchange Program in Statistical and Data Sciences

The Johns Hopkins - Nanjing University Exchange Program in Statistical and Data Sciences is funded by The Benjamin and Rhea Yeung Center for Collaborative China Studies.

 

Featured events:

1. From July 11 to July 22, 2011, the program will offer four 5-day summer training courses in biostatistics in Nanjing University, lectured by faculty from Johns Hopkins Department of Biostatistics. (See course schedules below).

2. Hopkins faculty will host a recruiting event in Nanjing during the week from July 11 to July 15, open to students from all universities. Students interested in applying for Hopkins Biostatistics graduate programs are welcome to attend and meet with our faculty team.

3. Top two Chinese students in the summer courses will be invited to visit Johns Hopkins for 9 months to do research with Hopkins faculty. Expense will be covered by the Yeung Center grant. The courses are free and open to students from all universities and institutions. However, to be qualified for the Hopkins exchange, students must register for the courses and must be affiliated with Nanjing University. Exchange students are expected to have strong mathematics, computer science, physics, life science, or engineering background.

4. The program will also invite one young faculty from Nanjing University to visit Hopkins for 6 months. Please send your CV and letters of recommendation to hji@jhsph.edu in order to be considered.

 

Introduction to Statistical Measurement and Modeling
Instructor: Karen Bandeen-Roche (Professor and Chair)

Time: July 11 - July 15, 2011. 9am-12noon
Description: The course will introduce concepts, theory and methods for describing, analyzing and interpreting statistical variation, characterizing measurement properties, and modeling relationships among variables.  The topics include an introduction to statistical reasoning; review of probability, random variable distributions and methods for parameter estimation; measures and methods for characterizing variability; and overview of correlation and association, linear regression modeling, and generalized linear regression modeling.  The course material extends to cover the synthesis of measurement and regression modeling in latent variable analysis.  Concepts will be illustrated using clinical and epidemiological data examples.  Students will gain familiarity with the definition and interpretation of the standard statistical regression and measurement models, methods of data display, procedures for deriving estimates of model parameters from data and making associated scientific inferences, and the role of statistics in biomedicine and public health.  

 

 

Statistical Computing
Instructor: Hongkai Ji (Assistant Professor)

Time: July 11 - July 15, 2011. 2pm-5pm
Description: Statistical modeling and inference have been greatly advanced by modern computing techniques. Statistical computing has become an indispensable tool for analyzing large scale data sets in genomics, imaging, environmental studies, as well as other fields. This course introduces the theory and application of commonly used algorithms in statistical computing. Topics include root finding, optimization, numerical integration, EM, MM, Monte Carlo, Markov chain Monte Carlo and Gibbs Sampling. The methods will be discussed in the context of current research problems. Students will be asked to implement key algorithms. Strong programming skills are recommended for taking this course.

 

 

Statistics for Genomics

Instructor: Rafael Irizarry (Professor, 2009 COPSS Presidents’ Award)

Time: July 18 - July 22, 2011. 9am-12noon
Description: We will give a brief introduction to genomics and molecular biology.

Then describe the technologies used to measure genomics outcomes focusing on microarrays and second-generation sequencing. We will then cover data analysis topics as they relate to preprocessing, normalization, detection of differential expression, SNP detection/genotyping, copy number variants, and epigenetics.

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Univariate and multivariate survival analysis
Instructor: Mei-Cheng Wang (Professor)

Time: July 18 - July 22, 2011. 2pm-5pm
Description: The course will introduce concepts, theory and methods for analyzing univariate and multivariate survival data. The topics include fundamental models and methods such as the Kaplan-Meier estimator, log-rank statistics and Cox regression model. The course material also extends to cover topics on length-bias and prevalent samplings, martingale theory, recurrent event processes and clustered survival data. The emphasis will be on nonparametric and semiparametric approaches for modeling, estimation and inferential results. Clinical and epidemiological data examples will be included in class presentation to illustrate statistical procedures.

 

 

 

Notice:

2011 Summer Courses in Nanjing

Location: 南京大学 仙林校区 仙2-505多媒体教室

Time: July11-15，18-22， 9 am-12 noon， 2 pm - 5 pm

(On Friday, July 15, the morning course will end at 11am, and the afternoon course will start at 2:30pm).

 

2011 Hopkins Biostatistics Recruiting Event at Nanjing

Location: 南京大学 仙林校区 仙2-505多媒体教室

Time: July 15，11 am-12:30pm