Joseph E. Gonzalez

Professor: I recently joined the EECS department at UC Berkeley as an assistant professor. My research interests are at the intersection of machine learning and data systems and explore the challenges of distributed learning and inference on large models and datasets, real-time model serving and personalization, and applying ML techniques to system tuning and management.

Co-founder: I am a co-founder of Dato Inc. (formerly GraphLab), which spun out of my thesis work on the GraphLab & PowerGraph Systems. At Dato we build software that enables data scientists to easily and efficiently extract signal from complex and noisy data and create intelligent applications and services.

Background: Before joining UC Berkeley as an assistant professor, I was a post-doc in the UC Berkeley AMPLab working on several projects including GraphX (now part of Apache Spark), early versions of MLbase, Velox, and concurrency control for ML. I got my PhD from the Machine Learning Department at Carnegie Mellon University where I worked with Carlos Guestrin on Parallel and Distributed Systems for Probabilistic Reasoning. I am a recipient of the AT&T Labs Graduate Research Fellowship and the National Science Foundation Graduate Research Fellowship.

Prospective Students

I am looking for additional graduate and undergraduate students to join my active projects on large-scale and real-time machine learning. If you are interested please send me an email and we can setup a time to meet.

I am in the process of updating this website with additional information on active projects, my research group, and teaching information so stay tuned!