Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Ihab Ilyas

Ihab Ilyas
Professor, Computer Science, University of Waterloo

Website | @ihabilyas

Ihab Ilyas is a professor in the Cheriton School of Computer Science at the University of Waterloo, where his research focuses on the areas of big data and database systems, with special interest in data quality and integration, managing uncertain data, rank-aware query processing, and information extraction. Ihab is also a cofounder of Tamr, a startup focusing on large-scale data integration and cleaning. He’s a recipient of the Ontario Early Researcher Award (2009), a Cheriton faculty fellowship (2013), an NSERC Discovery Accelerator Award (2014), and a Google Faculty Award (2014), and he’s an ACM Distinguished Scientist. Ihab is an elected member of the VLDB Endowment board of trustees and an associate editor of ACM Transactions of Database Systems (TODS). He holds a PhD in computer science from Purdue University, West Lafayette.

Sessions

14:05–14:45 Wednesday, 23 May 2018
Solving data cleaning and unification using human-guided machine learning
Data science and machine learning
 Location: Capital Suite 15/16 Level: Intermediate
Secondary topics:  Data Integration and Data Pipelines sessions
Ihab Ilyas (University of Waterloo)
Average rating: ****.
(4.40, 5 ratings)
Machine learning tools promise to help solve data curation problems. While the principles are well understood, the engineering details in configuring and deploying ML techniques are the biggest hurdle. Ihab Ilyas provides insight into various techniques and discusses how machine learning, human expertise, and problem semantics collectively can deliver a scalable, high-accuracy solution. Read more.