In this talk, Andy Pavlo will discuss the pressing unsolved problems in self-driving DBMSs. These include how to support training data collection, fast state changes, succinct state and action representations, and accurate reward observations. Andy will also present techniques on how to build a new autonomous DBMS or the steps needed to retrofit an existing one to enable automated control.
Andy is an Associate Professor of Databaseology in the Computer Science Department at Carnegie Mellon University. His (unnatural) infatuation with database systems has inadvertently caused him to incur several distinctions, such as the NSF CAREER (2019), a Sloan Fellowship (2018), and the ACM SIGMOD Jim Gray Dissertation Award (2014).
