Christian Kästner is a professor and the director of the Software Engineering PhD program at the School of Computer Science at Carnegie Mellon University. His research focuses primarily on software analysis and the boundaries of modularity, especially in the context of highly-configurable systems.
This talk is a call for more and better education at the intersection of software engineering and machine learning, as well as for more system-wide research on building software systems with machine-learning components. Christian Kästner will argue that truly a system-wide perspective is needed if we want to have any hope at making meaningful progress in building production systems with machine learning components in terms of safety, usability, fairness, or security.
