Christoph Lippert

Researcher, eScience

 

My research is focused on machine learning and statistics in genomics and genetics. I am especially interested in method development and applications of Gaussian processes and linear mixed models.

In this space I have mostly been working on methods for genome-wide association studies (GWAS).

We are always looking for PhD students with a strong background in machine learning, statistics, or bioinformatics who are interested in internship projects in our office in Los Angeles. If you are interested, write me an e-mail.

     

 

 

Software projects:

FaST-LMM

efficient method for population structure correction in GWAS

LIMIX

Flexible and efficient python library for mixed models involving single or multiple traits in genetics

Publications

    2014

    2013

    2012

    2011

    2010

    2009

    2008

    Past organized events: