Presented By O'Reilly and Cloudera
Make Data Work
Sept 29–Oct 1, 2015 • New York, NY
Robert Grossman

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


Robert Grossman is the Chief Research Information Officer (CRIO), a Professor in the Division of Biological Sciences, and the Director of the Center for Data Intensive Science (CDIS) at the University of Chicago. He leads a research group in bioinformatics that develops technology for managing and analyzing large genomic datasets. He is also the Founder and a Partner at Open Data Group, which has building predictive models over big data for its clients since 2002. He blogs occasionally about big data, data science, and data engineering at


11:20am–12:00pm Thursday, 10/01/2015
Data Science & Advanced Analytics
Location: 1 E8 / 1 E9 Level: Intermediate
Robert Grossman (University of Chicago)
Average rating: ****.
(4.25, 16 ratings)
Large datasets have large numbers of anomalies, and the challenge is not just identifying anomalies but rank ordering them to create alerts, so that data scientists can examine the most interesting ones. We discuss three case studies that integrate machine learning and data engineering, and extract six techniques for identifying anomalies and ranking ordering them by their potential significance. Read more.
1:15pm–1:55pm Thursday, 10/01/2015
Office Hours
Location: Table B (O'Reilly Booth)
Robert Grossman (University of Chicago)