May 31, 2017

Dr. Michael Gubanov Receives 2017 IEEE ICDE Best Paper Award




Photos of Gubanov (middle left), Jermaine, and Luo by Chaitan Baru, Senior Advisor for Data Science at the National Science Foundation

 

Photo of Gubanov (left center), Jermaine, and Luo by Chaitan Baru, Senior Advisor for Data Science at the National Science Foundation.

 

Dr. Michael Gubanov received the 2017 IEEE International Conference on Data Engineering (ICDE) Best Paper award for his work in large-scale data analytics together with researchers from Rice University. The annual IEEE ICDE is known as one of the most prestigious and competitive forums in data management research.

 

Gubanov describes a novel scalable data analytics system that supports both relational and linear algebras. The system represents not only a fundamental contribution to data management, but it also has many practical applications in business intelligence, healthcare, cyber security, and other areas. The demonstrated data management engine simplifies development of large-scale analytical workloads that use matrices and vectors in addition to tabular data representation, which is the de-facto standard in relational databases.

 

The paper can be found here: http://mgubanov.com/doc/H_icde.pdf

 

Gubanov is a Cloud Technology Endowed Assistant Professor at The University of Texas at San Antonio Department of Computer Science. His research interests include cloud computing, large-scale data management, web-search, and biomedical informatics. His other notable research accomplishments include new systems for information extraction from text (while at the University of Washington), data integration (while at IBM Research and M.I.T.), and large-scale machine learning and web-search (while at Google). Gubanov is a recipient of the 2015 NASHP Young Investigator award, the 2016 IEEE Sensors Best Paper Award, and the 2017 IEEE ICDE Best Paper Award.