Professors Khuzaima Daudjee and Sujaya Maiyya of the Cheriton School of Computer Science have been awarded $220,000 from the Ontario Research Fund–Research Infrastructure (ORF-RI) program. This amount was matched by the Canada Foundation for Innovation’s John R. Evans Leaders Fund (CFI-JELF), bringing total funding to $440,000.
“When we invest in research, we invest in our province’s future,” said Nolan Quinn, Minister of Colleges and Universities. “These critical investments will ensure Ontario’s researchers can continue making discoveries that drive key sectors, create good-paying jobs, and improve the lives of all Ontarians.”
The project, titled Scalable Infrastructure for Data-Intensive Systems, will address foundational challenges in managing and analyzing large-scale data.
“With combined support from the Ontario Research Fund and the Canada Foundation for Innovation, our students will be able to develop innovative systems that manage and analyze vast amounts of data,” said Professor Khuzaima Daudjee, the project’s principal investigator. “Our goal is to create scalable, efficient and secure data infrastructure that advances big data research as well as has a tangible impact on industry and society.”
This research is among the 22 projects receiving support from the Ontario Research Fund at the University of Waterloo.
Left to right: Professors Khuzaima Daudjee and Sujaya Maiyya
Professor Daudjee focuses on systems-oriented research. He and his students work at the intersection of systems and data management, particularly on building large-scale systems, storage and infrastructure in the cloud and on modern hardware.
Professor Maiyya’s research interests lie broadly in distributed systems and databases as well as in data privacy and security. She and her students design, prototype and evaluate protocols to manage large-scale data efficiently and securely.
More about this research
Data-intensive applications solve problems by storing and analyzing large, heterogeneous datasets. Data come from many sources, among them sensors, streaming video, satellite and medical imagery, and as such require special computing software and systems to effectively integrate their high volume into resolution processes.
The goal of this research is to develop scalable big data systems to manage and analyze these datasets, through two interrelated projects — the development of a dynamic, in-memory hybrid transactional and analytical processing data system, and the creation of scalable, privacy-preserving, oblivious datastores.
The infrastructure will allow development of new algorithms and systems to address current and future big data challenges. As solutions to many problems increasingly rely on data-driven approaches, managing and analyzing large data sets becomes increasingly important.
The expected outcomes including advancing state-of-the-art methods for scalable and secure big data management, delivering significant societal benefits both provincially and nationally. Technological innovations will be quickly transferred to industry. Furthermore, undergraduate and graduate students will be trained in cutting-edge big data techniques, equipping them with expertise required by industry. The infrastructure developed through this research will position Ontario and Canada as global leaders in big data research and development.