Presented By O'Reilly and Cloudera
Make Data Work
Feb 17–20, 2015 • San Jose, CA
Chris Re

Chris Re
Assistant Professor, Stanford University | Apple

Website | @HazyResearch

Christopher (Chris) Re is an assistant professor in the Department of Computer Science at Stanford University. The goal of his work is to enable users and developers to build applications that more deeply understand and exploit data. Chris received his PhD from the University of Washington in Seattle under the supervision of Dan Suciu. For his PhD work in probabilistic data management, Chris received the SIGMOD 2010 Jim Gray Dissertation Award. Chris’s papers have received four best-paper or best-of-conference citations, including best paper in PODS 2012, best-of-conference in PODS 2010 twice, and one best-of-conference in ICDE 2009). Chris received an NSF CAREER Award in 2011 and an Alfred P. Sloan fellowship in 2013.


9:00am–5:00pm Wednesday, 02/18/2015
Hardcore Data Science
Location: LL20 BC
Ben Lorica (O'Reilly Media), Ben Recht (University of California, Berkeley), Chris Re (Stanford University | Apple), Maya Gupta (Google), Alyosha Efros (UC Berkeley), Eamonn Keogh (University of California - Riverside), John Myles White (Facebook), Fei-Fei Li (Stanford University), Tara Sainath (Google), Michael Jordan (UC Berkeley), Anima Anandkumar (UC Irvine), John Canny (UC Berkeley), David Andrzejewski (Sumo Logic)
Average rating: ****.
(4.86, 7 ratings)
All-Day: Strata's regular data science track has great talks with real world experience from leading edge speakers. But we didn't just stop there—we added the Hardcore Data Science day to give you a chance to go even deeper. The Hardcore day will add new techniques and technologies to your data science toolbox, shared by leading data science practitioners from startups, industry, consulting... Read more.
4:30pm–5:00pm Wednesday, 02/18/2015
Hardcore Data Science
Location: LL20 BC.
Chris Re (Stanford University | Apple)
Average rating: *****
(5.00, 3 ratings)
We describe how DeepDive is being used in a range of tasks from diagnosing rare diseases to drug purposing to filling out the tree of life. DeepDive helps to create knowledge bases that meet--and sometimes even exceed--human-level quality and to perform predictive analytics on top of this data. Read more.