About

Robert L. Grossman I am the Chief Research Informatics Officer (CRIO), the Director of the Initiative in Data Intensive Science and a Professor in the Division of Biological Sciences at the University of Chicago. I am also a Core Faculty and Senior Fellow at the Institute for Genomics and Systems Biology (IGSB) and the Computation Institute. My research group focuses on big data, data science, bioinformatics, cloud computing and related areas.

I am also the Founder and a Partner of Open Data Group. Open Data Group has provided analytic services so that companies can build predictive models over big data since 2002.

I am the Chair of the not-for-profit Open Cloud Consortium, 
which develops and operates clouds to support research in science,
 medicine, health care, and the environment.

I can be reached via Linkedin Linkedin or Google+.

Recent Awards

Advisory Boards

  • From 2009 to the present, I have been a member of the NASA Advisory Council (NAC)’s Information Technology Infrastructure Committee.
  • From 2008 to the present, I have been the Director of the Open Cloud Consortium (OCC).
  • From 1998 to 2010, I was the Director of the Data Mining Group, which develops the Predictive Model Markup Language.
  • I was a Member of the Board of Directors of the ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) during the period 2005-2013.
  • From its founding in 1999 until 2003, I was a Member of Board of Directors of Infoblox (NYSE: BLOX).

Other Awards

  • Overall Winner, SC 09 Bandwidth Challenge. First Place, SC 08 Bandwidth Challenge.
    First Place, SC07 Analytics Challenge. First Place, SC 06 Bandwidth Challenge.
  • ACM SIGKDD 2007 Service Award for “… the development of open and scalable architectures and standards for the SIGKDD and Global KDD Communities.” SIGKDD is the ACM’s professional group on Knowledge Discovery and Data Mining.
  • First Place, 2007 Data Mining Practice Prize. A project I led was awarded First Place in the 2007 Data Mining Practice Prize at the ACM Conference on Knowledge Discovery and Data Mining (KDD 2007).