Skip to main content
Cornell university
Cornell Statistics and Data Science Cornell Statistics and Data Science
  • About Us

    About Us
    Cornell's Department of Statistics and Data Science offers four programs at the undergraduate and graduate levels. Undergraduates can earn a BA in statistical science, social...

    Welcome to the Department of Statistics and Data Science
    History
    Facilities
    Statistics Graduate Society
    Recently Published Papers
  • Academics

    Academics

    Undergraduate
    PhD
    MPS
    PhD Minor in Data Science
    Courses & Course Enrollment
  • People

    People

    Faculty
    Field Faculty
    PhDs
    Emeritus Faculty
    Academic Staff
    Staff
    Research Areas of Expertise
    Statistical Consultants
  • News and Events

    News and Events

    Events
    News
  • Resources

    Resources

    Professional Societies and Meetings
    Affiliated Groups
    Career Services
    Cornell Statistical Consulting Unit
  • Alumni

    Alumni
    Cornell's Statistics and Data Science degrees prepare students for a wide variety of careers, from academia to industry.  See the After Graduation page for a general overview of...

    Alumni Profiles

Search form

You are here

  1. Home 
  2. Events 
  3. Statistics Seminars

Statistics Seminar Speaker: Ruoqing Zhu, 04/17/2019

Event Layout

Wednesday Apr 17 2019

Statistics Seminar Speaker: Ruoqing Zhu, 04/17/2019

4:15pm @ G01 Biotechnology
In Statistics Seminars

The Statistics Seminar speaker for Wednesday, April 17, 2019, is Ruoqing Zhu, an Assistant Professor of Statistics at the University of Illinois at Urbana Champaign. Dr. Zhu received his Ph.D. of Biostatistics in 2013 from the University of North Carolina at Chapel Hill and worked as a postdoctoral research associate at Yale University. His research focuses on random forests, personalized medicine, survival analysis, high-dimensional data analysis, and dimension reduction. He is a recipient of the NCSA (National Center for Supercomputing Applications) Fellowship and a course associate director at the Carle Illinois College of Medicine.

Talk: Dimension reduction for Personalized Dose Finding

Abstract: Learning an individualized dose rule (IDR) in personalized medicine is a challenging statistical problem. Existing methods for estimating the optimal IDR often suffer from the curse of dimensionality, especially when the IDR is learned nonparametrically using machine learning approaches. We propose a dimension reduction framework by exploiting that the IDR can be represented by a nonparametric function which relies only on a few linear combinations of the original covariates, leading to a more parsimonious model. To achieve this, we consider two approaches, a direct learning approach that yields the IDR as commonly desired in personalized medicine, and a pseudo-direct learning approach that focuses more on learning the dimension reduction space. Under regularity assumptions, we provide the convergence rate for the semiparametric estimators and Fisher consistency properties for the corresponding value function. In both approaches, we use an orthogonality constrained optimization approach on the Stiefel manifold to solve the dimension reduction space. Performances are evaluated through simulation studies and a warfarin pharmacogenetic study.

Event Categories

  • Statistics Seminars
  • Special Events

Image Gallery

Ruoqing Zhu
  • Home
  • About Us
  • Contact Us
  • Careers
© Cornell University Department of Statistics and Data Science

1198 Comstock Hall, 129 Garden Ave., Ithaca, NY 14853

Social Menu

  • Facebook
  • Twitter
  • YouTube
Cornell Bowers CIS College of Computing and Information Science Cornell CALS ILR School

If you have a disability and are having trouble accessing information on this website or need materials in an alternate format, contact web-accessibility@cornell.edu for assistance.