Joseph Gonzalez: at the intersection of machine learning and data systems

EECS Assistant Prof. Joseph Gonzalez is the focus of a profile for the Association for Computing Machinery’s “People of ACM” series.  Gonzalez, who works at the intersection of machine learning and data systems, desribes how and why his field has grown over time, where it might be heading, and what challenges might need to be addressed in the future.  “Today progress is largely limited by creativity and our budget for compute resources and data,” he says. “Machine learning frameworks…provide the necessary abstractions to hide the complexity of differentiation, optimization, and parallel computation, freeing the modern data scientist to focus on the learning problem. These frameworks build on advances in data systems and scientific computing to unlock new parallel hardware.”