Learning-based Algorithms in DBMS: Hype or Future?

Renata Borovica-Gajic - University of Melbourne

Feb. 11, 2022, 4 p.m. - Feb. 11, 2022, 5 p.m.

Virtual (see link below)

Hosted by: Oana Balmau

Abstract: Machine Learning has revolutionized many domains, and is nowadays used in a wide range of applications such as internet ad placement, e-commerce rating systems, credit risk in finance, health analytics, and smart utility grids. In this talk we will consider whether databases are next in line. I will briefly cover the trends that led to a quick uptake of machine learning within the database engines, as well as discuss the current road blockers that prevent broader adoption within commercial database management systems. Finally, I will conclude the talk with a couple of examples of my work on using machine learning for database performance tuning and indexing, including recent ICDE 2021, and ADC 2020 publications. 


Bio: Renata Borovica-Gajic holds a position of Senior Lecturer in Data Analytics in the School of Computing and Information Systems at The University of Melbourne. Dr Borovica-Gajic received her Ph.D. degree in Computer Science from Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland in 2016. Renata's research focuses on solving data management problems when storing, accessing and processing massive data sets, enabling faster, more predictable, and cheaper data analysis as a result. She envisions database systems as dynamic entities able to adjust query processing strategies to fit the characteristics of data and usage patterns. She is also interested in the topics of scientific data management, data exploration, query optimization, physical database design, and hardware-software co-design. Her work has repeatedly appeared in the premier data management conferences such as SIGMOD, VLDB, and ICDE.

Zoom link: https://mcgill.zoom.us/j/84280715850

Virtual reception after the talk in Gather: https://gather.town/app/tYHHMh7tPcPw9037/reception