Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA
Robert Grossman

Robert Grossman
Director, Center for Data Intensive Science, University of Chicago


Robert Grossman is a faculty member and the chief research informatics officer in the Biological Sciences Division of the University of Chicago. Robert is the director of the Center for Data Intensive Science (CDIS) and a senior fellow at both the Computation Institute (CI) and the Institute for Genomics and Systems Biology (IGSB). He is also the founder and a partner of the Open Data Group, which specializes in building predictive models over big data. Robert has led the development of open source software tools for analyzing big data (Augustus), distributed computing (Sector), and high-performance networking (UDT). In 1996, he founded Magnify, Inc., which provides data-mining solutions to the insurance industry and was sold to ChoicePoint in 2005. He is also the chair of the Open Cloud Consortium, a not-for-profit that supports the research community by operating cloud infrastructure, such as the Open Science Data Cloud. He blogs occasionally about big data, data science, and data engineering at


2:40pm3:20pm Wednesday, March 15, 2017
Data science & advanced analytics
Location: 230 C Level: Intermediate
Secondary topics:  Hardcore Data Science, Healthcare
Robert Grossman (University of Chicago)
Average rating: ***..
(3.73, 11 ratings)
When there is a strong signal in a large dataset, many machine-learning algorithms will find it. On the other hand, when the effect is weak and the data is large, there are many ways to discover an effect that is in fact nothing more than noise. Robert Grossman shares best practices so that you will not be accused of p-hacking. Read more.