Michele Guindani

Assistant Professor
Department of Biostatistics
UT MD Anderson Cancer Center

Adjunct Assistant Professor, Department of Statistics, Rice University, Houston, TX
Associate Member, The University of Texas Graduate School of Biomedical Sciences at Houston

Link to my institutional webpage

Link to the Official Webpage of the ISBA 2016 World Meeting

Short Bio

I received my Ph.D. at Universita' Bocconi, Milan, Italy, in 2005.

During my PhD, I visited for a year the Department of Statistical Sciences at Duke University, where afterward I spent some months as Research Assistant.

I have been a postdoctoral fellow at the Department of Biostatistics at the MD Anderson Cancer Center from 2005 to 2007.

I have been an Assistant Professor in Statistics at the Department of Mathematics and Statistics at the University of New Mexico from August 2007 to June 2010.

I joined again the Department of Biostatistics at  the MD Anderson Cancer Center as an Assistant Professor in Biostatistics in the July 2010.

Current Service to the Profession

Member of  Program Council of the International Society of Bayesian Analysis (ISBA) (2014-2016)
Program chair of ISBA (2015)
Program chair of the Scientific Committee of the ISBA 2016 World Meeting

Associate editor for Bayesian Analysis and Computational Statistics and Data Analysis

Departments currently supported

Anesthesiology & Perioperative Medicine, Critical Care, Pain Medicine, Respiratory Care, Genetics, Melanoma Medical Oncology, Epidemiology, Nursing Rehabilitation, General Internal Medicine, Pulmonary Medicine, Pediatrics, Thoracic & Cardiovascular Surgery. I am also collaborating with investigators in Behavioral Science and Clinical Cancer Prevention

Current Research Interests (keywords)

Analysis of high-dimensional data, including genomic and imaging data. Data integration for combining information from several  data platforms, and relating them with measurable outcomes (integrative genomics, imaging genomics), statistical decision making under uncertainty, multiple comparison problems, clustering, Bayesian modeling, Bayesian Nonparametrics.